Technical ReportPDF Available

Science of the Heart, Volume 2 Exploring the Role of the Heart in Human Performance An Overview of Research Conducted by the HeartMath Institute

Authors:

Abstract and Figures

This insightful and comprehensive monograph provides fundamental and detailed summaries of HeartMath Institute’s many years of innovative research. It presents brief overviews of heart rate variability, resilience, coherence, heart-brain interactions,intuition and the scientific discoveries that shaped techniques developed to increase fulfillment and effectiveness. Included are summary reports of research conducted in the business, education, health and first responder fields. Both the layperson and science professional will appreciate its simplicity and thoroughness.
Content may be subject to copyright.
of the
HEART
SCIENCE
Exploring the Role of the
Heart in Human Performance
An overview of research conducted by HeartMath Institute
Volume 2
SCIENCE OF THE HEART
Exploring the Role of the Heart in Human Performance
Volume 2
Authored by Rollin McCraty, Ph.D.
Director of Research, HeartMath Research Center
Phone: (831) 338-8500
Email: info@heartmath.org
Visit our website at https://www.heartmath.org
Published by: HeartMath Institute
HeartMath Institute
14700 West Park Ave.
P.O. Box 1463
Boulder Creek, CA 95006
Distributed in USA by HeartMath Institute
Copyright © 2015 by HeartMath Institute
Cover and layout design by Sandy Royall
Volume 1 2001
Volume 2 2015
ISBN 978-1-5136-0636-1 Paperback
All rights reserved. No part of this book may be translated or reproduced in any form
without the written permission of HeartMath Institute.
HeartMath®, Freeze Frame®, Heart Lock-In®, Cut-Thru®, Inner Quality Management® (IQM)
are registered trademarks of HeartMath Institute.
10 9 8 7 6 5 4 3 2 1
First printing, November 2015
i
© Copyright 2015 HeartMath Institute
Table of Contents
About HeartMath Institute ............................................................................................................ iii
Introduction .....................................................................................................................................1
Chapter 1: Heart-brain Communication ......................................................................................... 3
Chapter 2: Resilience, Stress and Emotions .................................................................................8
Chapter 3: Heart Rate Variability: An Indicator of Self-Regulatory Capacity,
Autonomic Function and Health ..................................................................................................13
Chapter 4: Coherence ...................................................................................................................24
Chapter 5: Establishing a New Baseline ......................................................................................29
Chapter 6: Energetic Communication ..........................................................................................36
Chapter 7: Intuition Research: Coherence and the Surprising Role of the Heart ......................45
Chapter 8: Health Outcome Studies ............................................................................................53
Chapter 9: Outcome Studies in Education ..................................................................................66
Chapter 10: Social Coherence: Outcome Studies in Organizations ...........................................81
Chapter 11: Global Coherence Research: Human-Earth Interconnectivity ................................89
Bibliography ................................................................................................................................100
ii
© Copyright 2015 HeartMath Institute
HeartMath Institute (HMI) is an innovative nonprot research and education or-
ganization that provides simple, user-friendly mental and emotion self-regulation
tools and techniques that people of all ages and cultures can use in the moment
to relieve stress and break through to greater levels of personal balance, stability,
creativity, intuitive insight and fulllment.
HMI research has formed the foundation for training programs conducted
around the world in many different types of populations, including major cor-
porations, government and social-service agencies, all branches of the Armed
Forces, schools and universities, hospitals and a wide range of health-care
professionals. The tools and technologies developed at HMI offer hope for
new, effective solutions to the many daunting problems that society currently
faces, beginning with restoring balance and maximizing the potential within
each of us.
HeartMath Institute’s Mission (HMI)
The mission of HeartMath Institute is to help people bring their physical, men-
tal and emotional systems into balanced alignment with their heart’s intuitive
guidance. This unfolds the path for becoming heart-empowered individuals who
choose the way of love, which they demonstrate through compassionate care
for the well-being of themselves, others and Planet Earth.
About HeartMath Institute
iii
© Copyright 2015 HeartMath Institute
1
© Copyright 2015 HeartMath Institute
Introduction
New research shows the human heart is much more than an ecient pump that sustains life.
Our research suggests the heart also is an access point to a source of wisdom and intelligence
that we can call upon to live our lives with more balance, greater creativity and enhanced in-
tuitive capacities. All of these are important for increasing personal effectiveness, improving
health and relationships and achieving greater fulllment.
This overview will explore intriguing aspects of the science of the heart, much of which is still
relatively not well known outside the elds of psychophysiology and neurocardiology. We will
highlight research that bridges the science of the heart and the highly practical, research-based
skill set known as the HeartMath System.
The heart has been considered the source of emotion, courage and wisdom for centuries. For more than 25
years, the HeartMath Institute Research Center has explored the physiological mechanisms by which the
heart and brain communicate and how the activity of the heart inuences our perceptions, emotions, intuition
and health. Early on in our research we asked, among other questions, why people experience the feeling or
sensation of love and other regenerative emotions as well as heartache in the physical area of the heart. In the
early 1990s, we were among the rst to conduct research that not only looked at how stressful emotions affect
the activity in the autonomic nervous system (ANS) and the hormonal and immune systems, but also at the
effects of emotions such as appreciation, compassion and care. Over the years, we have conducted many studies
that have utilized many different physiological measures such as EEG (brain waves), SCL (skin conductance),
ECG (heart), BP (blood pressure) and hormone levels, etc. Consistently, however, it was heart rate variability,
or heart rhythms that stood out as the most dynamic and reective indicator of one’s emotional states and,
therefore, current stress and cognitive processes. It became clear that stressful or depleting emotions such as
frustration and overwhelm lead to increased disorder in the higher-level brain centers and autonomic nervous
system and which are reected in the heart rhythms and adversely affects the functioning of virtually all bodily
systems. This eventually led to a much deeper understanding of the neural and other communication pathways
between the heart and brain. We also observed that the heart acted as though it had a mind of its own and could
signicantly inuence the way we perceive and respond in our daily interactions. In essence, it appeared that
the heart could affect our awareness, perceptions and intelligence. Numerous studies have since shown that
heart coherence is an optimal physiological state associated with increased cognitive function, self-regulatory
capacity, emotional stability and resilience.
We now have a much deeper scientic understanding of many of our original questions that explains how and
why heart activity affects mental clarity, creativity, emotional balance, intuition and personal effectiveness. Our
and others’ research indicates the heart is far more than a simple pump. The heart is, in fact, a highly complex
Introduction
2
© Copyright 2015 HeartMath Institute
Science of the Heart
information-processing center with its own functional brain, commonly called the heart brain, that communicates
with and inuences the cranial brain via the nervous system, hormonal system and other pathways. These
inuences affect brain function and most of the body’s major organs and play an important role in mental and
emotional experience and the quality of our lives.
In recent years, we have conducted a number of research studies that have explored topics such as the elec-
trophysiology of intuition and the degree to which the heart’s magnetic eld, which radiates outside the body,
carries information that affects other people and even our pets, and links people together in surprising ways.
We also launched the Global Coherence Initiative (GCI), which explores the interconnectivity of humanity with
Earth’s magnetic elds.
This overview discusses the main ndings of our research and the fascinating and important role the heart
plays in our personal coherence and the positive changes that occur in health, mental functions, perception,
happiness and energy levels as people practice the HeartMath techniques. Practicing the techniques increases
heart coherence and one’s ability to self-regulate emotions from a more intuitive, intelligent and balanced inner
reference. This also explains how coherence is reected in our physiology and can be objectively measured.
The discussion then expands from physiological coherence to coherence in the context of families, workplaces
and communities. Science of the Heart concludes with the perspective that being responsible for and increasing
our personal coherence not only improves personal health and happiness, but also feeds into and inuences
a global eld environment. It is postulated that as increasing numbers of people add coherent energy to the
global eld, it helps strengthen and stabilize mutually benecial feedback loops between human beings and
Earth’s magnetic elds.
3
© Copyright 2015 HeartMath Institute
Heart-Brain Communication
The heart communicates with the brain and body in four ways:
• Neurological communication (nervous system)
• Biochemical communication (hormones)
• Biophysical communication (pulse wave)
• Energetic communication (electromagnetic elds)
Traditionally, the study of communication pathways between the head and heart has been approached from
a rather one-sided perspective, with scientists focusing primarily on the heart’s responses to the brain’s
commands. We have learned, however, that communication between the heart and brain actually is a dynamic,
ongoing, two-way dialogue, with each organ continuously inuencing the other’s function. Research has shown
that the heart communicates to the brain in four major ways: neurologically (through the transmission of nerve
impulses), biochemically (via hormones and neurotransmitters), biophysically (through pressure waves) and
energetically (through electromagnetic eld interactions). Communication along all these conduits signicantly
affects the brain’s activity. Moreover, our research shows that messages the heart sends to the brain also can
affect performance.
Some of the rst researchers in the eld of psycho-
physiology to examine the interactions between the
heart and brain were John and Beatrice Lacey. During
20 years of research throughout the 1960s and ’70s,
they observed that the heart communicates with the
brain in ways that signicantly affect how we perceive
and react to the world.
In physiologist and researcher Walter Bradford Can-
non’s view, when we are aroused, the mobilizing part
of the nervous system (sympathetic) energizes us for
ght or ight, which is indicated by an increase in heart
rate, and in more quiescent moments, the calming
part of the nervous system (parasympathetic) calms
us down and slows the heart rate. Cannon believed
the autonomic nervous system and all of the related
physiological responses moved in concert with the
brain’s response to any given stimulus or challenge.
Presumably, all of our inner systems are activated to-
gether when we are aroused and calm down together
when we are at rest and the brain is in control of the
entire process. Cannon also introduced the concept
of homeostasis. Since then, the study of physiology
has been based on the principle that all cells, tissues
and organs strive to maintain a static or constant
steady-state condition. However, with the introduc-
tion of signal-processing technologies that can ac-
quire continuous data over time from physiological
processes such as heart rate (HR), blood pressure
(BP) and nerve activity, it has become abundantly ap-
parent that biological processes vary in complex and
nonlinear ways, even during so-called steady-state
conditions. These observations have led to the under-
standing that healthy, optimal function is a result of
continuous, dynamic, bidirectional interactions among
multiple neural, hormonal and mechanical control
systems at both local and central levels. In concert,
these dynamic and interconnected physiological and
psychological regulatory systems are never truly at
rest and are certainly never static.
Heart-Brain Communication
CHAPTER 1
4
© Copyright 2015 HeartMath Institute
Science of the Heart
For example, we now know that the normal resting rhythm of the heart is highly variable rather than monoto-
nously regular, which was the widespread notion for many years. This will be discussed further in the section
on heart rate variability (HRV).
Figure 1.1 Innervation of the major organs by the autonomic nervous system (ANS). Parasympathetic bers are primarily in the
vagus nerves, but some that regulate subdiaphragmatic organs travel through the spinal cord. The sympathetic bers also travel
through the spinal cord. A number of health problems can arise in part because of improper function of the ANS. Emotions can
affect activity in both branches of the ANS. For example, anger causes increased sympathetic activity while many relaxation
techniques increase parasympathetic activity.
The Laceys noticed that the model proposed by Can-
non only partially matched actual physiological be-
havior. As their research evolved, they found that the
heart in particular seemed to have its own logic that
frequently diverged from the direction of autonomic
nervous system activity. The heart was behaving as
though it had a mind of its own. Furthermore, the
heart appeared to be sending meaningful messages
to the brain that the brain not only understood, but
also obeyed. Even more intriguing was that it looked
as though these messages could affect a person’s
perceptions, behavior and performance. The Laceys
identied a neural pathway and mechanism whereby
input from the heart to the brain could inhibit or fa-
cilitate the brain’s electrical activity. Then in 1974,
French researchers stimulated the vagus nerve (which
carries many of the signals from the heart to the brain)
in cats and found that the brain’s electrical response
was reduced to about half its normal rate.[1] This sug-
gested that the heart and nervous system were not
simply following the brain’s directions, as Cannon had
thought. Rather, the autonomic nervous system and
the communication between the heart and brain were
much more complex, and the heart seemed to have
its own type of logic and acted independently of the
signals sent from the brain.
While the Laceys research focused on activity occur-
ring within a single cardiac cycle, they also were able
to conrm that cardiovascular activity inuences
perception and cognitive performance, but there were
still some inconsistencies in the results. These in-
consistencies were resolved in Germany by Velden
and Wölk, who later demonstrated that cognitive
performance uctuated at a rhythm around 10 hertz
throughout the cardiac cycle. They showed that the
modulation of cortical function resulted from ascend-
ing cardiovascular inputs on neurons in the thalamus,
which globally synchronizes cortical activity.[2, 3] An
important aspect of their work was the nding that
5
© Copyright 2015 HeartMath Institute
it is the pattern and stability of the heart’s rhythm of
the afferent (ascending) inputs, rather than the num-
ber of neural bursts within the cardiac cycle, that are
important in modulating thalamic activity, which in
turn has global effects on brain function. There has
since been a growing body of research indicating that
afferent information processed by the intrinsic cardiac
nervous system (heart-brain) can inuence activity
in the frontocortical areas[4-6] and motor cortex,[7] af-
fecting psychological factors such as attention level,
motivation,[8] perceptual sensitivity[9] and emotional
processing.[10]
Neurocardiology: The Brain On the Heart
While the Laceys were conducting their research in
psychophysiology, a small group of cardiologists
joined forces with a group of neurophysiologists and
neuroanatomists to explore areas of mutual interest.
This represented the beginning of the new discipline
now called neurocardiology. One of their early ndings
is that the heart has a complex neural network that is
suciently extensive to be characterized as a brain on
the heart (Figure 1.2).[11, 12] The heart-brain, as it is com-
monly called, or intrinsic cardiac nervous system, is an
intricate network of complex ganglia, neurotransmit-
ters, proteins and support cells, the same as those of
the brain in the head. The heart-brain’s neural circuitry
enables it to act independently of the cranial brain to
learn, remember, make decisions and even feel and
sense. Descending activity from the brain in the head
via the sympathetic and parasympathetic branches
of the ANS is integrated into the heart’s intrinsic ner-
vous system along with signals arising from sensory
neurons in the heart that detect pressure, heart rate,
heart rhythm and hormones.
The anatomy and functions of the intrinsic cardiac ner-
vous system and its connections with the brain have
been explored extensively by neurocardiologists.[13, 14]
In terms of heart-brain communication, it is generally
well-known that the efferent (descending) pathways
in the autonomic nervous system are involved in the
regulation of the heart. However, it is less appreciated
that the majority of bers in the vagus nerves are
afferent (ascending) in nature. Furthermore, more of
these ascending neural pathways are related to the
heart (and cardiovascular system) than to any other
organ.[15] This means the heart sends more information
to the brain than the brain sends to the heart. More
recent research shows that the neural interactions
between the heart and brain are more complex than
previously thought. In addition, the intrinsic cardiac
nervous system has both short-term and long-term
memory functions and can operate independently of
central neuronal command.
Figure 1.2. Microscopic image of interconnected intrinsic
cardiac ganglia in the human heart. The thin, light-blue
structures are multiple axons that connect the ganglia.
Courtesy of Dr. J. Andrew Armour.
Once information has been processed by the heart’s
intrinsic nervous system, the appropriate signals are
sent to the heart’s sinoatrial node and to other tis-
sues in the heart. Thus, under normal physiological
conditions, the heart’s intrinsic nervous system plays
an important role in much of the routine control of
cardiac function, independent of the central nervous
system. The heart’s intrinsic nervous system is vital
for the maintenance of cardiovascular stability and
eciency and without it, the heart cannot function
properly. The neural output, or messages from the
intrinsic cardiac nervous system travels to the brain
via ascending pathways in the both the spinal column
and vagus nerves, where it travels to the medulla, hy-
pothalamus, thalamus and amygdala and then to the
cerebral cortex.[5, 16, 17] The nervous-system pathways
between the heart and brain are shown in Figure 1.3
and the primary afferent pathways in the brain are
shown in Figure 1.4.
Chapter 1: Heart-Brain Communication
6
© Copyright 2015 HeartMath Institute
Science of the Heart
Had the existence of the intrinsic cardiac nervous
system and the complexity of the neural communica-
tion between the heart and brain been known while
the Laceys were conducting their paradigm-shifting
research, their theories and data likely would have
been accepted far sooner. Their insight, rigorous ex-
perimentation and courage to follow where the data
led them, even though it did not t the well-entrenched
beliefs of the scientic community of their day, were
pivotal in the understanding of the heart-brain con-
nection. Their research played an important role in
elucidating the basic physiological and psychologi-
cal processes that connect the heart and brain and
the mind and body. In 1977, Dr. Francis Waldropin,
director of the National Institute of Mental Health,
stated in a review article of the Laceys’ work, “Their
intricate and careful procedures, combined with their
daring theories, have produced work that has stirred
controversy as well as promise. In the long run, their
research may tell us much about what makes each of
us a whole person and may suggest techniques that
can restore a distressed person to health.
Cortex
Subcortical Areas
Medulla
Spinal Cord
(Sympathetic)
Dorsal Root
Ganglion
Nodose Ganglion
Intrinsic Nervous System
SA Node
Chemosensory Neurons
Sympathetic & parasympathetic outputs to
muscles throughout the heart
Sympathetic
Parasympathetic
Afferent Pathways
Vagus Nerves
(Parasympathetic)
Mechanosensory Neurons
AV Node
Extrinsic Cardiac Ganglia
(Thoracic Cavity)
Heart-Brain
Communication Pathways
Brain
Heart
Figure 1.3. The neural communication pathways interacting between the heart and brain are responsible for the generation of HRV.
The intrinsic cardiac nervous system integrates information from the extrinsic nervous system and the sensory neurites within the
heart. The extrinsic cardiac ganglia located in the thoracic cavity have connections to the lungs and esophagus and are indirectly
connected via the spinal cord to many other organs, including the skin and arteries. The vagus nerve (parasympathetic) primarily
consists of afferent (owing to the brain) bers that connect to the medulla. The sympathetic afferent nerves rst connect to the
extrinsic cardiac ganglia (also a processing center), then to the dorsal root ganglion and the spinal cord. Once afferent signals
reach the medulla, they travel to the subcortical areas (thalamus, amygdala, etc.) and then the higher cortical areas.
7
© Copyright 2015 HeartMath Institute
Figure 1.4. Diagram of the currently known afferent pathways by which information from the heart and cardiovascular system
modulates brain activity. Note the direct connections from the NTS to the amygdala, hypothalamus and thalamus. Although not
shown, there also is evidence emerging that there is a pathway from the dorsal vagal complex that travels directly to the frontal
cortex.
The Heart as a Hormonal Gland
In addition to its extensive neurological interactions,
the heart also communicates with the brain and body
biochemically by way of the hormones it produces.
Although not typically thought of as an endocrine
gland, the heart actually manufactures and secretes
a number of hormones and neurotransmitters that
have a wide-ranging impact on the body as a whole.
The heart was reclassied as part of the hormonal
system in 1983, when a new hormone produced and
secreted by the atria of the heart was discovered. This
hormone has been called by several different names
– atrial natriuretic factor (ANF), atrial natriuretic pep-
tide (ANP) and atrial peptide. Nicknamed the balance
hormone, it plays an important role in uid and elec-
trolyte balance and helps regulate the blood vessels,
kidneys, adrenal glands and many regulatory centers
in the brain.[18] Increased atrial peptide inhibits the
release of stress hormones,[19] reduces sympathetic
outow[20] and appears to interact with the immune
system.[21] Even more intriguing, experiments suggest
atrial peptide can inuence motivation and behavior.[22]
It was later discovered the heart contains cells that
synthesize and release catecholamines (norepi-
nephrine, epinephrine and dopamine), which are
neurotransmitters once thought to be produced only
by neurons in the brain and ganglia.[23] More recently,
it was discovered the heart also manufactures and
secretes oxytocin, which can act as a neurotransmit-
ter and commonly is referred to as the love or social-
bonding hormone. Beyond its well-known functions
in childbirth and lactation, oxytocin also has been
shown to be involved in cognition, tolerance, trust
and friendship and the establishment of enduring
pair-bonds. Remarkably, concentrations of oxytocin
produced in the heart are in the same range as those
produced in the brain.[24]
Chapter 1: Heart-Brain Communication
8
© Copyright 2015 HeartMath Institute
Science of the Heart
An early editorial on the relationships between stress
and the heart accepted the proposition that in about
half of patients, strong emotional upsets precipitated
heart failure. Unspecied negative emotional arousal,
often described as stress, distress or upset, has been
associated with a variety of pathological conditions,
including hypertension,[26, 27] silent myocardial isch-
emia,[28] sudden cardiac death,[29] coronary disease,[30-32]
cardiac arrhythmia,[33] sleep disorders,[34] metabolic
syndrome,[35] diabetes,[36, 37] neurodegenerative diseas-
es,[38] fatigue[39, 40] and many other disorders.[41] Stress
and negative emotions have been shown to increase
disease severity and worsen prognosis for individuals
suffering from a number of different pathologies.[42, 43]
On the other hand, positive emotions and effective
emotion self-regulation skills have been shown to
prolong health and signicantly reduce premature
mortality.[44-49] From a psychophysiological perspec-
tive, emotions are central to the experience of stress.
It is the feelings of anxiety, irritation, frustration, lack
of control, and hopelessness that are actually what we
experience when we describe ourselves as stressed.
Whether it’s a minor inconvenience or a major life
change, situations are experienced as stressful to the
extent that they trigger emotions such as annoyance,
irritation, anxiety and overwhelm.[50]
In essence, stress is emotional unease, the experience
of which ranges from low-grade feelings of emotional
unrest to intense inner turmoil. Stressful emotions
clearly can arise in response to external challenges
or events, and also from ongoing internal dialogs and
attitudes. Recurring feelings of worry, anxiety, anger,
judgment, resentment, impatience, overwhelm and
self-doubt often consume a large part of our energy
and dull our day-to-day life experiences.
Resilience, Stress and Emotions
As far back as the middle of the last century, it was recognized that the heart, overtaxed by constant emo-
tional inuences or excessive physical effort and thus deprived of its appropriate rest, suffers disorders of
function and becomes vulnerable to disease.[25]
Additionally, emotions, much more so than thoughts
alone, activate the physiological changes compris-
ing the stress response. Our research shows a purely
mental activity such as cognitively recalling a past
situation that provoked anger does not produce nearly
as profound an effect on physiological processes as
actually engaging the emotion associated with that
memory. In other words, reexperiencing the feeling of
anger provoked by the memory has a greater effect
than thinking about it.[51, 52]
Resilience and Emotion Self-Regulation
Our emotions infuse life with a rich texture and trans-
form our conscious experience into a meaningful
living experience. Emotions determine what we care
about and what motivates us. They connect us to
others and give us the courage to do what needs to
be done, to appreciate our successes, to protect and
support the people we love and have compassion and
kindness for those who are in need of our help. Emo-
tions are also what allow us to experience the pain
and grief of loss. Without emotions, life would lack
meaning and purpose.
Emotions and resilience are closely related because
emotions are the primary drivers of many key physi-
ological processes involved in energy regulation. We
dene resilience as the capacity to prepare for, recover
from and adapt in the face of stress, adversity, trauma or
challenge.[53] Therefore, it follows that a key to sustain-
ing good health, optimal function and resilience is the
ability to manage one’s emotions.
It has been suggested that resilience should be
considered as a state rather than a trait and that a
person’s resilience can vary over time as demands,
CHAPTER 2
9
© Copyright 2015 HeartMath Institute
circumstances and level of maturity change.[54] In
our resilience training programs, we suggest that
the ability to build and sustain resilience is related to
self-management and ecient utilization of energy
resources across four domains: physical, emotional,
mental and spiritual (Figure 2.1). Physical resilience
is basically reected in physical exibility, endurance
and strength, while emotional resilience is reected in
the ability to self-regulate, degree of emotional ex-
ibility, positive outlook and supportive relationships.
Mental resilience is reected in the ability to sustain
focus and attention, mental exibility and the capac-
ity for integrating multiple points of view. Spiritual
resilience is typically associated with commitment to
core values, intuition and tolerance of others’ values
and beliefs.
Figure 2.1. Domains of Resilience.
By learning self-regulation techniques that allow us
to shift our physiology into a more coherent state,
the increased physiological eciency and alignment
of the mental and emotional systems accumulates
resilience (energy) across all four energetic domains.
Having a high level of resilience is important not only
for bouncing back from challenging situations, but
also for preventing unnecessary stress reactions
(frustration, impatience, anxiety), which often lead to
further energy and time waste and deplete our physi-
cal and psychological resources.
Most people would agree it is the ability to adjust and
self-regulate one’s responses and behavior that is
most important in building and maintaining support-
ive, loving relationships and effectively meeting life’s
demands with composure, consistency and integrity.
Chapter 2: Resilience, Stress and Emotions
The ability to adjust and self-regulate also is central to
resilience, good health and effective decision-making.
[55] It is a key for success in living life with greater kind-
ness and compassion in all relationships. If people’s
capacity for intelligent, self-directed regulation is
strong enough, then regardless of inclinations, past
experiences or personality traits, they usually can do
the adaptive or right thing in most situations.[56]
___________________________
We are coming to understand health not as the
absence of disease, but rather as the process by
which individuals maintain their sense of coher-
ence (i.e. sense that life is comprehensible, man-
ageable, and meaningful) and ability to function
in the face of changes in themselves and their
relationships with their environment.[57]
___________________________
It has been shown that our efforts to self-regulate emo-
tions can produce broad improvements in increasing
or strengthening self-regulatory capacity, similar to
the process of strengthening a muscle, making us
less vulnerable to depletion of our internal reserves.[56]
When internal energy reserves are depleted, normal
capacity to maintain self-control is weakened, which
can lead to increased stress, inappropriate behaviors,
lost opportunities, poor communication and damaged
relationships. Despite the importance of self-directed
control, many people’s ability to self-regulate is far less
than ideal. In fact, failures in self-regulation, especially
of emotions and attitudes, arguably are central to the
vast majority of personal and social problems that
plague modern societies. For some, the lack of self-
regulatory capacity can be attributed to immaturity or
failure to acquire skills while for others it can be the
result of trauma or impairment in the neural systems
that underlie one’s ability to self-regulate.[58] Therefore,
we submit the most important skill the majority of
people need to learn is how to increase their capacity
to self-regulate emotions, attitudes and behaviors.
Self-regulation enables people to mature and meet
the challenges and stresses of everyday life with re-
silience so they can make more intelligent decisions
by aligning with their innate higher-order wisdom and
10
© Copyright 2015 HeartMath Institute
Science of the Heart
expression of care and compassion, elements we often
associate with living a more conscientious life.
Our research suggests a new inner baseline reference
can be established by using the HeartMath (HM)
self-regulation techniques that help people replace
depleting emotional undercurrents with more posi-
tive, regenerative attitudes, feelings and perceptions.
A growing body of compelling scientific evidence is demonstrating a link between mental and
emotional attitudes, physiological health and long-term well-being:
60% to 80% of primary care doctor visits are related
to stress, yet only 3% of patients receive stress
management help.
[60-62]
In a study of 5,716 middle-aged people, those with the
highest self-regulation abilities were over 50 times more
likely to be alive and without chronic disease 15 years
later than those with the lowest self-regulation scores.
[63]
Positive emotions are a reliable predictor of better
health, even for those without food or shelter while
negative emotions are a reliable predictor of worse
health even when basic needs like food, shelter and
safety are met.
[64]
A Harvard Medical School Study of 1,623 heart attack
survivors found that when subjects became angry
during emotional conflicts, their risk of subsequent
heart attacks was more than double that of those who
remained calm.
[65]
A review of 225 studies concluded that positive
emotions promote and foster sociability and activity,
altruism, strong bodies and immune systems, effective
conflict resolution skills, success and thriving.
[66]
A study of elderly nuns found that those who expressed
the most positive emotions in early adulthood lived an
average of 10 years longer.
[67]
Men who complain of high anxiety are up to six times
more likely than calmer men to suffer sudden cardiac
death.
[68]
In a groundbreaking study of 1,200 people at high risk of
poor health, those who learned to alter unhealthy mental
and emotional attitudes through self-regulation training
were over four times more likely to be alive 13 years later
This new baseline, which will be summarized in a
later section, can be thought of as a type of implicit
memory that organizes perception, feelings and be-
havior.[5, 59] The process of establishing a new base-
line takes place at the physiological level, which is
imperative for sustained and lasting change to occur.
than an equal-sized control group.
[69]
A 20-year study of over 1,700 older men conducted by
the Harvard School of Public Health found that worry
about social conditions, health and personal nances
all signicantly increased the risk of coronary heart
disease.
[70]
Over one-half of heart disease cases are not explained
by the standard risk factors such as high cholesterol,
smoking or sedentary lifestyle.
[71]
An international study of 2,829 people ages 55 to 85
found that individuals who reported the highest levels
of personal mastery – feelings of control over life
events – had a nearly 60% lower risk of than those who
felt relatively helpless in the face of life’s challenges.
[72]
According to a Mayo Clinic study of individuals with
heart disease, psychological stress was the strongest
predictor of future cardiac events such as cardiac death,
cardiac arrest and heart attacks.
[73]
Three 10-year studies concluded that emotional
stress was more predictive of death from cancer and
cardiovascular disease than from smoking; people who
were unable to effectively manage their stress had a
40% higher death rate than nonstressed individuals.
[74]
A study of heart attack survivors showed that patients’
emotional states and relationships in the period after
myocardial infarction were as important as the disease
severity in determining their prognosis.
[75]
Separate studies showed that the risk of developing
heart disease is signicantly increased for people who
impulsively vent their anger as well as for those who
tend to repress angry feelings.
[76, 77]
11
© Copyright 2015 HeartMath Institute
Cognitive and Emotional System Integration
Dating back to the ancient Greeks, human thinking and
feeling, intellect and emotion have been considered
separate functions. These contrasting aspects of
the soul, as the Greeks called them, often have been
portrayed as being engaged in a constant battle for
control of the human psyche. In Plato’s view, emotions
were like wild horses that had to be reined in by the
intellect and willpower.
Research in neuroscience conrms that emotion and
cognition can best be thought of as separate but in-
teracting functions and systems that communicate
via bidirectional neural connections between the
neocortex, the body and emotional centers such as
the amygdala and body.[78] These connections allow
emotion-related input to modulate cortical activity
while cognitive input from the cortex modulates emo-
tional processing. However, the neural connections
that transmit information from the emotional centers
to the cognitive centers in the brain are stronger and
more numerous than those that convey information
from the cognitive to the emotional centers. This fun-
damental asymmetry accounts for the powerful inu-
ence of input from the emotional system on cognitive
functions such as attention, perception and memory
as well as higher-order thought processes. Conversely,
the comparatively limited inuence of input from the
cognitive system on emotional processing helps ex-
plain why it is generally dicult to willfully modulate
emotions through thought alone.
There can be differences from one individual to the
next in these reciprocal connections and interactions
between the cognitive and emotional systems that
affect the way we perceive, experience and eventually
remember our emotional experiences, and how we
respond to emotionally challenging situations. Unbal-
anced interactions between the emotional and cog-
nitive systems can lead to devastating effects such
as those observed in mood and anxiety disorders.[78]
Although there has been a historical bias favoring
the viewpoint that emotions interfere with and can
be at odds with rational thinking, which of course can
occur in some cases, emotions have their own type
of rationality and have been shown to be critical in
decision-making.[79] For example, Damasio points out,
patients with damage in areas of the brain that inte-
grate the emotional and cognitive systems can no lon-
ger effectively function in the day-to-day world, even
though their mental abilities are perfectly normal. In
the mid-1990s, the concept of emotional intelligence
was introduced, precipitating persuasive arguments
that the viewpoint of human intelligence being es-
sentially mind intellect was far too narrow. This was
because it ignored a range of human capacities that
bear equal if not greater weight in determining our
successes in life. Qualities such as self-awareness,
motivation, altruism and compassion, but especially
one’s ability to self-regulate and control impulses and
self-direct emotions were found to be as important or
more important than a high IQ. Those qualities, more
so than IQ, enable people to excel in the face of life’s
challenges.[80]
It is our experience that the degree of alignment be-
tween the mind and emotions can vary considerably.
When they are out of sync, it can result in radical
behavior changes that cause us to feel like there are
two different people inside the same body. It can also
result in confusion, diculty in making decisions,
anxiety and a lack of alignment with our deeper core
values. Conversely, when the mind and emotions are
in sync, we are more self-secure and aligned with our
deeper core values and respond to stressful situations
with increased resilience and inner balance.
Our research indicates that the key to the successful
integration of the mind and emotions lies in increasing
one’s emotional self-awareness and the coherence of,
or harmonious function and interaction among, the
neural systems that underlie cognitive and emotional
experience.[5, 58, 81]
As will be discussed in more detail in a later section,
we use the terms cardiac coherence, physiological
coherence and heart coherence interchangeably to
describe the measurement of the order, stability and
harmony in the oscillatory outputs of the body’s regu-
latory systems during any period of time.
Chapter 2: Resilience, Stress and Emotions
12
© Copyright 2015 HeartMath Institute
Science of the Heart
An important aspect of understanding how to in-
crease self-regulatory capacity and the balance
between the cognitive and emotional systems is the
inclusion of the heart’s ascending neuronal inputs
on subcortical (emotional) and cortical (cognitive)
structures which, as discussed above, can have
signicant inuences on cognitive resources and
emotions. Information is conveyed in the patterns
of the heart’s rhythms (HRV), that reects current
emotional states. The patterns of afferent neural
input (coherence and incoherence) to the brain af-
fect emotional experience and modulate cortical
function and self-regulatory capacity. We have found
that intentional activation of positive emotions plays
an important role in increasing cardiac coherence
and thus self-regulatory capacity.[5] These ndings
expand on a large body of research into the ways
positive emotional states can benet physical, men-
tal and emotional health.[44-49]
Because emotions exert such a powerful inuence on
cognitive activity, intervening at the emotional level
is often the most ecient way to initiate change in
mental patterns and processes. Our research demon-
strates that the application of emotion self-regulation
techniques along with the use of facilitative technol-
ogy (emWave®, Inner Balance™) can help people bring
the heart, mind and emotions into greater alignment.
Greater alignment is associated with improved deci-
sion-making, creativity, listening ability, reaction times
and coordination and mental clarity.[81]
13
© Copyright 2015 HeartMath Institute
Heart Rate Variability: An Indicator of Self-Regulatory
Capacity, Autonomic Function and Health
The autonomic nervous system (ANS) (Figure 1.1) is the part of the nervous system that controls the body’s
internal functions, including heart rate, gastrointestinal tract and secretions of many glands. The ANS also
controls many other vital activities such as respiration, and it interacts with immune and hormonal system
functions. It is well known that mental and emotional states directly affect activity in the ANS.
The autonomic nervous system must be considered
as a complex system in which both efferent (descend-
ing) and afferent (ascending) vagal (parasympathetic)
neurons regulate adaptive responses. Considerable
evidence suggests evolution of the ANS, specically
the vagus nerves, was central to development of emo-
tional experience, the ability to self-regulate emotional
processes and social behavior and that it underlies
the social engagement system. As human beings,
we are not limited to ght, ight, or freeze responses.
We can self-regulate and initiate pro-social behaviors
when we encounter challenges, disagreements and
stressors. The healthy function of the social engage-
ment system depends upon the proper functioning
of the vagus nerves, which act as a vagal brake. This
system underlies one’s ability to self-regulate and
calm oneself by inhibiting sympathetic outow to
targets like the heart and adrenal glands. This implies
that measurements of vagal activity could serve as a
marker for one’s ability to self-regulate. This also sug-
gests that the evolution and healthy function of the
ANS determines the boundaries for the range of one’s
emotional expression, quality of communication and
the ability to self-regulate emotions and behaviors.[82]
Many of HMI’s research studies have examined the
inuence of emotions on the ANS utilizing analysis
of heart rate variability/heart rhythms, which reects
heart-brain interactions and autonomic nervous sys-
tem dynamics.[5, 83]
The investigation of the heart’s complex rhythms,
or HRV began with the emergence of modern signal
processing in the 1960s and 1970s and has rap-
idly expanded in more recent times.[84] The irregular
HRV: An Indicator of Self-Regulatory Capacity, Autonomic Function and Health
behavior of the heartbeat is readily apparent when
heart rate is examined on a beat-to-beat basis, but is
overlooked when a mean value over time is calculated.
These uctuations in heart rate result from complex,
nonlinear interactions among a number of different
physiological systems (Figure 3.1).
Figure 3.1. Heart rate variability is a measure of the
normally occurring beat-to-beat changes in heart rate. The
electrocardiogram (ECG) is shown on the bottom and the
instantaneous heart rate is shown by the blue line. The time
between each of the heartbeats (blue line) between 0 and
approximately 13 seconds becomes progressively shorter and
heart rate accelerates and then starts to decelerate around
13 seconds. This pattern of heart-rate accelerations and
decelerations is the basis of the heart’s rhythms.
An optimal level of HRV within an organism reects
healthy function and an inherent self-regulatory ca-
pacity, adaptability, and resilience.[5, 58, 59, 85-88] While
too much instability, such as arrhythmias or nervous
system chaos, is detrimental to ecient physiological
functioning and energy utilization, too little variation
indicates age-related system depletion, chronic stress,
pathology or inadequate functioning in various levels
of self-regulatory control systems.[84, 89, 90]
CHAPTER 3
14
© Copyright 2015 HeartMath Institute
Science of the Heart
The importance of HRV as an index of the functional
status of physiological control systems was noted as
far back as 1965, when it was found that fetal distress
was preceded by reductions in HRV before any changes
occurred in heart rate.[91] In the 1970s, reduced HRV
was shown to predict autonomic neuropathy in diabetic
patients before the onset of symptoms.[92-94] Reduced
HRV also was found to be a higher risk factor of death
post-myocardial infarction than other known risk fac-
tors.[95] It has been shown that HRV declines with age
and that age-adjusted values should be used in the
context of risk prediction.[96] Age-adjusted HRV that is
low has been conrmed as a strong, independent pre-
dictor of future health problems in both healthy people
and in patients with known coronary artery disease and
correlates with all-cause mortality.[97, 98]
Based on indirect evidence, reduced HRV may cor-
relate with disease and mortality because it reects
reduced regulatory capacity and ability to adapt/
respond to physiological challenges such as exercise.
For example, in the Chicago Health, Aging and Social
Relations Study, separate metrics for the assessment
of autonomic balance and overall cardiac autonomic
regulation were developed and tested in a sample
of 229 participants. In this study, overall regulatory
capacity was a signicant predictor of overall health
status, but autonomic balance was not. In addition,
cardiac regulatory capacity was negatively associ-
ated with the prior incidence of myocardial infarc-
tions. The authors suggest that cardiac regulatory
capacity reects a physiological state that is more
relevant to health than the independent sympathetic
or parasympathetic controls, or the autonomic bal-
ance between these controls as indexed by different
measures of HRV.[99]
Heart rate variability also indicates psychological
resiliency and behavioral exibility, reecting an indi-
vidual’s capacity to self-regulate and effectively adapt
to changing social or environmental demands.[99, 100]
A growing number of studies have specically linked
vagally mediated HRV to self-regulatory capacity,[87, 88,
101] emotional regulation,[102, 103] social interactions,[86, 104]
one’s sense of coherence[105] and the personality charac-
ter traits of self-directedness[106] and coping styles.[107]
More recently, several studies have shown an associa-
tion between higher levels of resting HRV and perfor-
mance on cognitive performance tasks requiring the
use of executive functions.[89] HRV coherence (described
later) can be increased in order to improve cognitive
function[5, 108-110] as well as a wide range of clinical out-
comes, including reduced health-care costs.[59, 111-116]
Self-Regulation: Cortical Systems
Considerable evidence from clinical, physiological and
anatomical research has identied cortical, subcorti-
cal and medulla oblongata structures involved in car-
diac regulation. Oppenheimer and Hopkins mapped a
detailed hierarchy of cardiac control structures among
the cortex, amygdala and other subcortical structures,
all of which can modify cardiovascular-related neurons
in the lower levels of the neuraxis (Figure 3.2).[117]
Figure 3.2. Schematic diagram showing the relationship of
the principal descending neural pathways from the insular and
prefrontal cortex to subcortical structures and the medulla
oblongata as outlined by Oppenheimer and Hopkins.
[117]
The insular and prefrontal cortexes are key sites involved in
modulating the heart’s rhythm, particularly during emotionally
charged circumstances. These structures along with other
centers such as the orbitofrontal cortex and cingulate gyrus
can inhibit or enhance emotional responses. The amygdala
is involved with refined integration of emotional content
in higher centers to produce cardiovascular responses
that are appropriate for the emotional aspects of current
circumstances. Imbalances between the neurons in the insula,
amygdala and hypothalamus may initiate cardiac rhythm
disturbances and arrhythmias. The structures in the medulla
represent an interface between incoming afferent information
from the heart, lungs and other bodily systems and outgoing
efferent neuronal activity.
[117]
15
© Copyright 2015 HeartMath Institute
They suggest that the amygdala is involved with rened
integration of emotional content in higher centers
to produce cardiovascular responses that are ap-
propriate for the emotional aspects of the current
circumstances. The insular cortex and other centers
such as the orbitofrontal cortex and cingulate gyrus
can overcome (self-regulate) emotionally entrained
responses by inhibiting or enhancing them. They
also point out that imbalances between the neurons
in the insula, amygdala and hypothalamus may initi-
ate cardiac rhythm disturbances and arrhythmias.
The data suggests that the insular and medial pre-
frontal cortexes are key sites involved in modulating
the heart’s rhythm, particularly during emotionally
charged circumstances.
Thayer and Lane also have described the same set of
neural structures outlined by Oppenheimer and Hop-
kins, which they call the central autonomic network
(CAN). The CAN is involved in cognitive, emotional
and autonomic regulation, which they linked directly
to HRV and cognitive performance. In their model, the
CAN links the nucleus of tractus solitarius in the me-
dulla with the insula, prefrontal cortex, amygdala and
hypothalamus through a series of feedback and feed-
forward loops. They also propose that this network is
an integrated system for internal self-regulation by
which the brain controls the heart and other internal
organs, neuroendocrine and behavioral responses that
are critical for goal-directed behavior, adaptability and
sustained health. They suggest that these dynamic
connections explain why parasympathetically (va-
gal) mediated HRV is linked to higher-level executive
functions and reects the functional capacity of the
brain structures that support working memory and
emotional and physiological self-regulation. They have
shown that higher levels of vagally mediated HRV are
correlated with prefrontal cortical performance and
the ability to inhibit unwanted memories and intrusive
thoughts. The prefrontal cortex can be taken oine
when individuals perceive that they are threatened,
and prolonged periods of prefrontal cortical inactiv-
ity can lead to hypervigilance, defensiveness and
social isolation. During these decreases in prefrontal
cortical activation, heart rate (HR) increases and HRV
decreases.[89]
Thoughts and even subtle emotions influence
the activity in the autonomic nervous system.
The ANS interacts with our digestive, cardio-
vascular, immune, hormonal and many other
bodily systems.
Negative emotions/feelings create disorder in
the brain’s regulatory systems and ANS.
Feelings such as appreciation create increased
order in the brain’s regulatory systems and ANS,
resulting in improved hormonal- and immune-sys-
tem function and enhanced cognitive function.
The nucleus of tractus in the medulla oblongata inte-
grates afferent sensory information from propriocep-
tors (body position), chemoreceptors (blood chemis-
try) and mechanoreceptors, also called baroreceptors,
(pressure or distortion) from the heart, lungs and face.
The nucleus of tractus connects to the dorsal motor
nucleus of the vagus nerve and the nucleus ambiguus.
Neurocardiology research indicates that the descend-
ing vagal bers that innervate the heart are primarily
A-bers, which are the largest and fastest conducting
axons that originate from nerve cells located primarily
in the nucleus ambiguus. The nucleus ambiguus also
receives and integrates information from the cortical
and subcortical systems described above.[118] Thus,
the vagal regulatory centers respond to peripheral sen-
sory (afferent) inputs and higher brain-center inputs to
adjust neuronal outows, which results in the vagally
mediated beat-to-beat changes in HR.
Increased efferent activity in the vagal nerves (also
called the 10th cranial nerve) slows HR and increases
bronchial tone. The vagus nerves are the primary
nerves for the parasympathetic system and they in-
nervate the intrinsic cardiac nervous system. A few of
these connections synapse on motor neurons in the
intrinsic cardiac nervous system and these neurons
project directly to the SA node (and other tissues in
the heart), where they trigger acetylcholine release
to slow HR.[11] However, the majority of the efferent
preganglionic vagal neurons (~80%) connect to lo-
cal circuitry neurons in the intrinsic cardiac nervous
system, where motor information is integrated with
Chapter 3: HRV: An Indicator of Self-Regulatory Capacity, Autonomic Function and Health
16
© Copyright 2015 HeartMath Institute
Science of the Heart
inputs from mechanosensory and chemosensory
neurons in the heart.[119] Thus, efferent sympathetic
and parasympathetic activity is integrated in and with
the activity occurring in the heart’s intrinsic nervous
system, including the input signals from the mecha-
nosensory and chemosensory neurons within the
heart, all of which ultimately contribute to beat-to-beat
cardiac functional changes.[17]
In summary, the cardiorespiratory control system is
complex and information from many inputs is inte-
grated at multiple levels of the system, all of which
are important for the generation of normal beat-to-
beat variability in HR and BP. The medulla oblongata
is the major structure integrating incoming afferent
information from the heart, lungs and face with inputs
from cortical and subcortical structures and is the
source of the respiratory modulation of the activity
patterns in sympathetic and parasympathetic out-
ow. The intrinsic cardiac nervous system integrates
mechanosensitive and chemosensitive neuron inputs
with efferent information from both the sympathetic
and parasympathetic inputs from the brain, and as a
complete system affects HRV, vasoconstriction and
cardiac contractility in order to regulate HR and blood
pressure.[120]
HRV and Analysis Methods
The normal variability in heart rate results from the
descending (efferent) and the ascending (afferent)
activity occurring in the two branches of the ANS,
which act in concert, along with mechanical, hormonal
and other physiological mechanisms to maintain car-
diovascular parameters in their optimal ranges and to
permit appropriate adjustments to changing external
and internal conditions and challenges (Figure 1.3).
At rest, both sympathetic and parasympathetic nerves
are tonically active, with the vagal effects predomi-
nant. Therefore, heart rate best reects the relative
balance between the sympathetic and parasympa-
thetic systems. When speaking of autonomic bal-
ance, it should be kept in mind that a healthy system
is constantly and dynamically changing. Therefore,
an important indicator of the health status of the
regulatory systems is that they have the capacity to
respond to and adjust the relative autonomic balance,
as reected in heart rate, to the appropriate state for
whatever a person is engaged in at any given moment.
In other words, does the HR dynamically respond
and is it higher in the daytime or when dealing with
challenging tasks and lower when at rest or during
sleep? Inability of the physiological self-regulatory
systems to adapt to the current context and situation
is associated with numerous clinical conditions.[121]
Also, distinct, altered, circadian patterns in 24-hour
heart rates are associated with different and specic
psychiatric disorders, particularly during sleep.[122, 123]
Heart rate estimated at any given time represents the
net effect of the neural output of the parasympathetic
(vagus) nerves, which slows HR and the sympathetic
nerves, which accelerate it. In a denervated human
heart in which there are no connections from the ANS
to the heart following its transplantation, the intrinsic
rate generated by a pacemaker (SA node) is about
100 BPM.[124] Parasympathetic activity predominates
when HR is below this intrinsic rate during normal
daily activities and when at rest or sleep. When HR
is above ~100 BPM, the relative balance shifts and
sympathetic activity predominates. The average 24-
hour HR in healthy people is ~73 BPM. Higher HRs are
independent markers of mortality in a wide spectrum
of conditions.[121]
It is important to note the natural relationship between
HR and amount of HRV. As HR increases there is less
time between heartbeats for variability to occur, so
HRV decreases, while at lower HRs there is more time
between heartbeats, so variability naturally increases.
This is called cycle length dependence, and it persists
in the healthy elderly to a variable degree, even at
very advanced ages. However, elderly patients with
ischemic heart disease or other pathologies increas-
ingly have less variability as HRs decrease, ultimately
losing the relationship between HR and variability – to
the point that variability does not increase at all with
reductions in HR.[125] Even in healthy subjects, the
effects of cycle length dependence should be taken
into account when assessing HRV, and HR values
should always be reported, especially when HRs are
increased because of factors such as stress reactions,
medications and physical activity.
17
© Copyright 2015 HeartMath Institute
An increase in sympathetic activity is the principal
method used to increase HR above the intrinsic level
generated by the SA node. Activation of this branch
of the ANS, in concert with the activation of the en-
docrine system, facilitates the ability to respond to
challenges, stressors or threats by increasing the
mobilization of energy resources.
Following the onset of sympathetic stimulation, there
is a delay of up to 5 seconds before the stimulation
induces a progressive increase in HR, which reaches
a steady level in 20 to 30 seconds if the stimulus
is continuous.[120] The relatively slow response to
sympathetic stimulation is in direct contrast to vagal
stimulation, which is almost instantaneous. However,
the effect of sympathetic stimulation on HR is longer-
lasting and even a brief stimulus can affect HR for 5
to 10 seconds. Efferent (descending) sympathetic
nerves target the SA node via the intrinsic cardiac
nervous system and the bulk of the myocardium
(heart muscle). Action potentials conducted by these
motor neurons trigger norepinephrine and epinephrine
release, which increases HR and strengthens the
contractility of the atria and ventricles.
HRV can be assessed with various analytical ap-
proaches, although the most commonly used are
frequency domain (power spectral density) analysis
and time domain analysis. In both methods, the
time intervals between each successive normal QRS
complex are rst determined. All abnormal beats not
generated by the sinus node are eliminated from the
record. The interactions between autonomic neural
activity, BP, respiratory and higher-level control sys-
tems produce both short- and long-term rhythms in
HRV measurements.[5, 126, 127] The most common form
for observing these changes is the heart-rate tacho-
gram, a plot of the sequence of time intervals between
heartbeats (Figure 3.3).
Chapter 3: HRV: An Indicator of Self-Regulatory Capacity, Autonomic Function and Health
Figure 3.3. An example of the heart-rate tachogram, a plot of the sequence of time intervals between heartbeats over an 8-hour
period in ambulatory recording taken from a 36-year-old male. Each of the traces is one hour long, with the starting time of the
hour on the left-hand side of the gure. The time between each vertical line is 5 minutes. The vertical axis within each of the hourly
tracings is the time between heartbeats (interbeat intervals) ranging from 400 tp 1,200 milliseconds (label shown on second
row). A 15-minute period of HRV coherence can be seen in the latter part of the hour, starting at 19:30 when this man practiced
HeartMath’s Heart Lock-In
®
Technique. The latter part of the hour, starting at 23:30, is typical of restful sleep.
18
© Copyright 2015 HeartMath Institute
Science of the Heart
Power spectral analysis is used to separate the com-
plex HRV waveform into its component rhythms (Fig-
ure 3.4). Spectral analysis provides information about
how power is distributed (the variance and amplitude
of a given rhythm) as a function of frequency (the
time period of a given rhythm). The main advantages
of spectral analysis over the time domain measures
are that it supplies both frequency and amplitude
information on the specic rhythms that exist in the
HRV waveform, providing a means to quantify these
oscillations over any given period. The values are
expressed as the power spectral density, which is the
area under the curve (peak) in a given bandwidth of the
spectrum. The power or height of the peak at any given
frequency indicates the amplitude and stability of the
rhythm. The frequency reects the period of time over
which the rhythm occurs. For example, a 0.1 hertz fre-
quency has a period of 10 seconds. In order to under-
stand how power spectral analysis distinguishes the
various underlying physiological mechanisms re-
ected in the heart’s rhythm, a brief discussion of
the underlying physiological mechanisms is helpful.
The power spectrum is divided into three main fre-
quency ranges.
High-Frequency Band
The high-frequency (HF) spectrum is the power in the
range from 0.15 to 0.4 hertz, which equates to rhythms
with periods that occur between 2.5 and 7 seconds.
This band reects parasympathetic or vagal activity
and is frequently called the respiratory band because
it corresponds to the HR variations related to the
respiratory cycle known as respiratory sinus arrhyth-
mia. The mechanisms linking the variability of HR to
respiration are complex and involve both central and
reex interactions.[118] During inhalation, the cardio-
respiratory center inhibits vagal outow, resulting in
speeding up HR. Conversely, during exhalation, vagal
outow is restored, resulting in slowing HR.[128] The
magnitude of the oscillation is variable, but in healthy
people, it can be increased by slow, deep breathing.
Figure 3.4. This gure shows a typical HRV recording over a 15-minute period during resting conditions in a healthy individual.
The top trace shows the original HRV waveform. Filtering techniques were used to separate the original waveform into VLF, LF,
and HF bands as shown in the lower traces. The bottom of the gure shows the power spectra (left) and the percentage of power
(right) in each band.
19
© Copyright 2015 HeartMath Institute
Reduced parasympathetic (HF) activity has been
found in a number of cardiac pathologies as discussed
earlier. In terms of psychological regulation, reduced
vagally mediated HRV has been linked to reduced
self-regulatory capacity and cognitive functions that
involve the executive centers of the prefrontal cortex.
This is consistent with the nding that lower HF power
is associated with stress, panic and anxiety/worry.
Lower parasympathetic activity, rather than reduced
sympathetic functioning, appears to account for a
higher ratio of the reduced HRV in aging.[96]
Low-Frequency Band
The low-frequency (LF) band ranges between 0.04 and
0.15 hertz, which equates to rhythms or modulations
with periods that occur between 7 and 25 seconds.
This region was previously called the baroreceptor
range or midfrequency band by many researchers
because it primarily reects baroreceptor activity
while at rest.[129] As discussed previously, the vagus
nerves are a major conduit through which afferent
neurological signals from the heart are relayed to the
brain, including baroreex signals. Baroreceptors are
stretch-sensitive mechanoreceptors located in the
chambers of the heart and vena cavae, carotid sinuses
(which contain the most sensitive mechanoreceptors)
and the aortic arch. Baroreex gain is commonly cal-
culated as the beat-to-beat change in HR per unit of
change in BP. Decreased baroreex gain is related to
aging and impaired regulatory capacity.
The existence of a cardiovascular system resonance
frequency, which is caused by the delay in the feed-
back loops in the baroreex system, has long been
established. When the cardiovascular system oscil-
lates at this frequency, there is a distinctive high-
amplitude peak in the HRV power spectrum around
0.1 hertz. Most mathematical models show that the
resonance frequency of the human cardiovascular
system is determined by the feedback loops between
the heart and brain.[130, 131] In humans and many other
mammals, the resonance frequency of the system is
approximately 0.1 hertz, equivalent to a 10-second
rhythm, which is also characteristic of the coherent
state described earlier.
Chapter 3: HRV: An Indicator of Self-Regulatory Capacity, Autonomic Function and Health
The sympathetic nervous system does not appear
to have much inuence in rhythms above 0.1 hertz,
while the parasympathetic system can be observed to
affect heart rhythms down to 0.05 hertz (20-second
rhythm). Therefore, during periods of slow respira-
tion rates, vagal activity can easily generate oscil-
lations in the heart rhythms that cross over into the
LF band.[111, 132, 133] Thus, respiratory-related efferent
vagally mediated inuences are particularly present
in the LF band when respiration rates are below 8.5
breaths per minute/7-second periods or when an in-
dividual sighs or takes a deep breath.[133, 134]
In ambulatory 24-hour HRV recordings, it has been
suggested that the LF band reects sympathetic
activity and the LF/HF ratio has been used, contro-
versially so, to assess the balance between sympa-
thetic and parasympathetic activity.[135-137] A number
of researchers have challenged this perspective and
have persuasively argued that in resting conditions,
the LF band reects baroreex activity and not cardiac
sympathetic innervation.[40, 71, 96, 105-107]
The perspective that the LF band reects sympathetic
activity comes from observations of 24-hour ambula-
tory recordings in which there are frequent sympa-
thetic activations primarily resulting from physical
activity, but also emotional reactions, which can create
oscillations in the heart rhythms that cross over from
the VLF band into the lower region of the LF band. In
long-term ambulatory recordings, the LF band fairly
approximates sympathetic activity when increased
sympathetic activity occurs.[138] Unfortunately, some
authors have assumed that this interpretation also is
true of short-term resting recordings and have con-
fused slower breathing-related increases in LF power
with sympathetic activity, when in reality it is almost
entirely vagally mediated.
Very-Low-Frequency Band
The very-low-frequency band (VLF) is the power in
the HRV power spectrum range between 0.0033 and
0.04 hertz which equates to rhythms or modulations
with periods that occur between 25 and 300 seconds.
Although all 24-hour clinical measures of HRV reect-
ing low HRV are linked with increased risk of adverse
20
© Copyright 2015 HeartMath Institute
Science of the Heart
outcomes, the VLF band has stronger associations
with all-cause mortality than LF and HF bands.[98, 139-141]
Low VLF power has been shown to be associated
with arrhythmic death[142] and PTSD.[143] Additionally,
low power in this band has been associated with high
inammation[144, 145] in a number of studies and has
been correlated with low levels of testosterone, while
other biochemical markers, such as those mediated
by the HPA axis (e.g., cortisol), have not.[146] Longer
time periods using 24-hour HRV recordings should
be obtained to provide comprehensive assessment
of VLF and ULF uctuations.[147]
Historically, the physiological explanation and
mechanisms involved in the generation of the VLF
component have not been as well dened as the LF
and HF components. This region has been largely
ignored even though it is the most predictive of ad-
verse outcomes. Long-term regulation mechanisms
and ANS activity related to thermoregulation, the
renin-angiotensin system and other hormonal factors
appear to contribute to this band.[148, 149] Recent work
by Dr. J. Andrew Armour has shed new light on the
mechanisms underlying the VLF rhythm and suggests
that we have to reconsider both the mechanisms and
importance of this band.
This line of research began after some surprising
results from a study looking at HRV in autotrans-
planted hearts in dogs. In autotransplants, the heart
is removed and placed back in the same animal, so
there is no need for anti-rejection medications. The
primary purpose of the study was to determine if
the autonomic nerves reinnervated the heart post-
transplant. Monthly 24-hour HRV recordings were
done over a one-year period on all of the dogs with
autotransplanted hearts as well as control dogs. It
turned out that the nerves did reinnervate, but in a
way that was not accurately reected in HRV. It was
shown that the intrinsic cardiac nervous system had
neuroplasticity and restructured its neural connec-
tions. The truly surprising result was that these de-
innervated hearts had higher levels of HRV than the
control dogs immediately post-transplant and these
levels were sustained over a one-year period, includ-
ing HRV, which typically is associated with respiration
(Figure 3.5).[150] This was unexpected because in hu-
man transplant recipients, there is very little HRV.[151]
Autotransplant
Figure 3.5. Heart Rhythms Generated by a Transplanted Heart: At top left is the heart-rate tachogram of a dog after undergoing
cardiac autotransplantation, with the accompanying top-right graph showing the HRV power spectrum. For comparison, the
bottom graphs show the heart-rate tachogram and HRV power spectrum of a normal dog. Note the similarity between the two.
21
© Copyright 2015 HeartMath Institute
Following up on these results, Armour and colleagues
developed methods for obtaining long-term single-
neuron recordings from a beating heart and, simulta-
neously, from extrinsic cardiac neurons.[13] This work,
combined with later ndings by Kember and Armour,
implies that the VLF rhythm is generated by the
stimulation of afferent sensory neurons in the heart,
which in turn activates various levels of the feedback
and feed-forward loops in the heart’s intrinsic cardiac
nervous system, as well as between the heart and
neurons in the extrinsic cardiac ganglia and spinal
column.[152, 153] Thus, the VLF rhythm appears to be
produced by the heart itself and is an intrinsic rhythm
that appears to be fundamental to health and well-
being. Armour has observed that when the amplitude
of the VLF rhythm at the neural level is diminished in
an animal research subject, the animal is in danger and
will expire shortly if the research procedures proceed.
This cardiac origin of the VLF rhythm also is supported
by studies showing that sympathetic blockade does
not affect VLF power and VLF activity remains in
tetraplegics, whose sympathetic innervation of the
heart and lungs is disrupted.[154]
Circadian rhythms, core body temperature, metabo-
lism, hormones and intrinsic rhythms generated by the
heart all contribute to lower-frequency rhythms (e.g.,
very-low-frequency and ultra-low-frequency rhythms)
that extend below 0.04 hertz. In healthy individuals,
there is an increase in VLF power that occurs during
the night and peaks before waking.[155,156] This increase
in autonomic activity appears to correlate with the
morning cortisol peak.
To summarize, experimental evidence suggests the
VLF rhythm is intrinsically generated by the heart and
the amplitude and frequency of these oscillations are
modulated by efferent sympathetic activity. Normal
VLF power appears to indicate healthy function, and
increases in resting VLF power and/or shifting of fre-
quency can reect efferent sympathetic activity. The
modulation of the frequency of this rhythm resulting
from physical activity,[157] stress responses and other
factors that increase efferent sympathetic activation
can cause it to cross over into the lower region of the
LF band during ambulatory monitoring or during short-
Chapter 3: HRV: An Indicator of Self-Regulatory Capacity, Autonomic Function and Health
term recordings when there is a signicant emotional
stressor.[5]
Time Domain Measurements of HRV
Time domain indices quantify the amount of vari-
ance in the interbeat interval (IBI) using statistical
measures. Time domain measures are the simplest
to calculate. Time domain measures do not provide
a means to adequately quantify autonomic dynam-
ics or determine the rhythmic or oscillatory activity
generated by the different physiological control sys-
tems. However, since they are always calculated the
same way, data collected by different researchers are
comparable, but only if the recordings are exactly the
same length of time and the data are collected under
the same conditions. The three most important and
commonly reported time domain measures are the
SDNN, the SDNN index, and the RMSSD.
SDNN
The SDNN is the standard deviation of the normal-
to-normal (NN) sinus-initiated interbeat-intervals
measured in milliseconds. This measure reects the
ebb and ow of all the factors that contribute to HRV.
In 24-hour recordings, the SDNN is highly correlated
with ULF and total power.[96] In short-term resting
recordings, the primary source of the variation is
parasympathetically mediated, especially with slow,
deep-breathing protocols. However, in ambulatory and
longer-term recordings the SDNN values are highly
correlated with lower-frequency rhythms.[83] Thus, low
age-adjusted values predict morbidity and mortality.
For example, patients with moderate SDNN values
(50-100 milliseconds) have a 400% lower risk of mor-
tality than those with low values (0-50 milliseconds)
in 24-hour recordings.[158, 159]
SDNN Index
The SDNN index is the mean of the standard devia-
tions of all the NN intervals for each 5-minute seg-
ment. Therefore, this measurement only estimates
variability due to the factors affecting HRV within
a 5-minute period. In 24-hour HRV recordings, it is
calculated by rst dividing the 24-hour record into
288 ve-minute segments and then calculating the
22
© Copyright 2015 HeartMath Institute
Science of the Heart
standard deviation of all NN intervals contained
within each segment. The SDNN Index is the average
of these 288 values.[90] The SDNN index is believed to
primarily measure autonomic inuence on HRV. This
measure tends to correlate with VLF power over a
24-hour period.[83]
RMSSD
The RMSSD is the root mean square of successive
differences between normal heartbeats. This value
is obtained by rst calculating each successive time
difference between heartbeats in milliseconds. Each
of the values is then squared and the result is aver-
aged before the square root of the total is obtained.
The RMSSD reects the beat-to-beat variance in heart
rate and is the primary time domain measure used to
estimate the vagally mediated changes reected in
HRV. [90] The RMSSD is correlated with HF power and
therefore also reects self-regulatory capacity, as
discussed earlier.[83]
HRV Assessment Services
The Autonomic Assessment Report, (AAR), developed
by the HeartMath Research Center, provides physi-
cians, researchers and mental health-care profession-
als with a diagnostic tool to detect abnormalities and
imbalances in the autonomic nervous system and
predict those at increased risk of developing various
pathologies often before symptoms become mani-
fest. The HeartMath Research Center provides this
analysis service to physicians and medical institutions
throughout the U.S. and abroad.
The Autonomic Assessment Report is a powerful tool
for quantifying autonomic function. The AAR provides
health-care professionals and researchers with a non-
invasive test that quanties autonomic function and
relative balance and risk stratication, and assesses
the effects of interventions on autonomic function.
The AAR is derived from 24-hour am bulatory ECG
recordings, typically obtained with an “HRV” recorder,
which is inexpensive, lightweight and comfortable
to wear. The AAR is based on analysis of heart rate
variability, which provides a unique window into the
interactions of sympathetic and parasympathetic
control of the heart. The report includes time domain,
frequency domain and circadian rhythm analysis,
which together constitute a comprehensive analysis
of autonomic activity, relative balance and rhythms.
Time domain measures include the mean normal-
to-normal (NN) intervals during a 24-hour recording
and statistical measures of the variance between
NN intervals. Power spectral density analysis is used
to assess how power is distributed as a function of
frequency, providing a means to quantify autonomic
balance at any given point in the 24-hour period, as
well as to chart the circadian rhythms of activity in
the two branches of the autonomic nervous system.
HMI has established and maintains an extensive HRV
database of healthy individuals that greatly increases
the AAR’s value as a diagnostic and risk-assessment
tool. Additionally, the age and gender normative val-
ues are provided for each time and frequency domain
HRV value.
HRV is useful for monitoring autonomic function and
assessing ANS involvement in a number of clinical
conditions. Importantly, low HRV has been found to be
predictive of increased risk of heart disease, sudden
cardiac death as well as all-cause mortality.
Autonomic Function Imbalances Are
Associated With:
Depression Irritable Bowel
Hypoglycemia Fibromyalgia
Panic Disorder Hypertension
Sleep Disorder Chemical Sensitivity
Asthma Premenstrual Syndrome
Fatigue Anxiety
Dizziness Migraine
Nausea Arrhythmia
Autonomic imbalances have been implicated in a wide
variety of pathologies, including depression, fatigue,
premenstrual syndrome, hypertension, diabetes mel-
litus, ischemic heart disease, coronary heart disease
and environmental sensitivity. Stress and emotional
states have been shown to dramatically affect auto-
nomic function. Self-regulation techniques, which en-
able individuals to gain greater control of their mental
and emotional stress and improve their autonomic
23
© Copyright 2015 HeartMath Institute
functioning, can signicantly affect a wide variety
of disorders in which autonomic imbalance plays a
role. The AAR analysis is highly useful for the quan-
titative demonstration of the effects of HeartMath
interventions in restoring healthy autonomic function
in many patients who have been able to signicantly
improve their symptomatology and psychological
well-being through practice of these techniques.
Figure 3.6. Sample pages from the HeartMath Autonomic Assessment Report. Shown from top left to right are: (1) Summary
page with normative reference ranges. (2) 24-Hour Heart Rate Prole and Heart Rate Variability Index plot. (3) Autonomic Balance
Prole and frequency domain analysis summary. (4) Circadian Rhythm Analysis page and bottom graph. (5) One page of the three
heart-rate tachogram pages showing HRV from the full 24-hours.
Chapter 3: HRV: An Indicator of Self-Regulatory Capacity, Autonomic Function and Health
The Autonomic Assessment Report Interpretation Guide
and Instructions booklet, available from HMI, provides
clinicians with understandable descriptions of HRV
measures used in the report and how to interpret them
in clinical applications. It includes a number of case
histories and clinical examples.
24
© Copyright 2015 HeartMath Institute
Science of the Heart
Coherence
Denitions of Coherence
Clarity of thought, speech and emotional composure
The quality of being orderly, consistent and intelligible (e.g. a coherent sentence).
Synchronization or entrainment between multiple waveforms
A constructive waveform produced by two or more waves that are phase- or frequency-locked.
Order within a singular oscillatory waveform
An ordered or constructive distribution of power content within a single waveform; autocoherence (e.g. sine wave).
The various concepts and measurements embraced
under the term coherence have become central to elds
as diverse as quantum physics, cosmology, physiology
and brain and consciousness research.[59] Coherence
has several related denitions, all of which are ap-
plicable to the study of human physiology, social
interactions and global affairs. The most common
dictionary denition is the quality of being logically
integrated, consistent and intelligible, as in a coherent
statement.[159] A related meaning is the logical, orderly
and aesthetically consistent relationship among parts.
[159] Coherence always implies correlations, connect-
edness, consistency and ecient energy utilization.
Thus, coherence refers to wholeness and global
order, where the whole is greater than the sum of its
individual parts.
In physics, coherence also is used to describe the
coupling and degree of synchronization between
different oscillating systems. In some cases, when
two or more oscillatory systems operate at the same
basic frequency, they can become either phase- or
frequency-locked, as occurs between the photons
in a laser.[160] This type of coherence is called cross-
coherence and is the type of coherence that most
scientists think of when they use the term. In physiol-
ogy, cross-coherence occurs when two or more of the
body’s oscillatory systems, such as respiration and
heart rhythms, become entrained and operate at the
same frequency.
Another aspect of coherence relates to the dynamic
rhythms produced by a single oscillatory system.
The term autocoherence describes coherent activity
within a single system. An ideal example is a system
that exhibits sine-wavelike oscillations; the more
stable the frequency, amplitude and shape, the higher
the degree of coherence. When coherence is increased
in a system that is coupled to other systems, it can
pull the other systems into increased synchronization
and more ecient function.
Many contemporary scientists believe it is the underlying state of our physiological processes that de-
termines the quality and stability of the feelings and emotions we experience. The feelings we label as
positive actually reect body states that are coherent, meaning “the regulation of life processes becomes ef-
cient, or even optimal, free-owing and easy,[160] and the feelings we label as “negative,” such as anger, anxiety
and frustration are examples of incoherent states. It is important to note, however, these associations are not
merely metaphorical. For the brain and nervous system to function optimally, the neural activity, which encodes
and distributes information, must be stable and function in a coordinated and balanced manner. The various
centers within the brain also must be able to dynamically synchronize their activity in order for information to
be smoothly processed and perceived. Thus, the concept of coherence is vitally important for understanding
optimal function.
CHAPTER 4
25
© Copyright 2015 HeartMath Institute
Figure 4.1. The top graphs show an individual’s heart rate variability, pulse transit time and respiration patterns for 10 minutes.
At the 300-second mark, the individual did HeartMath’s Freeze Frame Technique and all three systems came into entrainment,
meaning the patterns were harmonious instead of scattered and out of sync. The bottom graphs show the spectrum analysis view
of the same data. The left-hand side is the spectral analysis before Freeze-Framing. Notice how each pattern looks quite different
from the others. The graphs on the right show how all three systems are entrained at the same frequency after Freeze-Framing.
Chapter 4: Coherence
Global Coherence
For any system to produce a meaningful function, it
must have the property of global coherence. In hu-
mans, this includes our physical, mental, emotional
and social systems. However, the energy eciency
and degree of coordinated action of any given system
can vary widely and does not necessarily result in a
coherent output or ow of behavior. Global coherence
does not mean everyone or all parts of a system are
doing the same thing simultaneously. In complex glob-
ally coherent systems, such as human beings, there is
a vast amount of activity at every level of magnica-
tion or scale that spans more than two-thirds of the 73
known octaves of the electromagnetic spectrum.[165]
It can appear at one level of scale that a given system
is operating autonomously, yet it is perfectly coordi-
nated within the whole. In living systems, there are
microlevel systems, molecular machines, protons
and electrons, organs and glands, each functioning
autonomously, doing very different things at different
rates, yet all working together in a complex harmoni-
ously coordinated and synchronized manner. If this
were not happening, it would be a free-for-all among
For example, frequency pulling and entrainment can easily be seen between the heart, respiratory and blood-
pressure rhythms as well as between very-low-frequency brain rhythms, craniosacral rhythms and electrical
potentials measured across the skin.[142, 143]
26
© Copyright 2015 HeartMath Institute
Science of the Heart
the body’s independent systems, rather than a coor-
dinated federation of interdependent systems and
functions. Biologist Mae-Won Ho has suggested that
coherence is the dening quality of living systems
and accounts for their most characteristic properties,
such as long-range order and coordination, rapid and
ecient energy transfer and extreme sensitivity to
specic signals.[165]
We introduced the term physiological coherence to
describe the degree of order, harmony and stability in
the various rhythmic activities within living systems
over any given time period.[163] This harmonious order
signies a coherent system, whose ecient or optimal
function is directly related to the ease and ow in life
processes. In contrast, an erratic, discordant pattern
of activity denotes an incoherent system whose func-
tion reects stress and inecient utilization of energy
in life processes. Specically, heart coherence (also
referred to as cardiac coherence or resonance) can be
measured by HRV analysis wherein a person’s heart-
rhythm pattern becomes more ordered and sine wave-
like at a frequency of around 0.1 hertz (10 seconds).
When a person is in a more coherent state there
is a shift in the relative autonomic balance toward
increased parasympathetic activity (vagal tone),
increased heart-brain synchronization and entrain-
ment between diverse physiological systems. In this
mode, the body’s systems function with a high degree
of eciency and harmony and natural regenerative
processes are facilitated. Although physiological
coherence is a natural human state that can occur
spontaneously, sustained episodes generally are
rare. While some rhythmic-breathing methods may
induce coherence for brief periods, our research in-
dicates that people can achieve extended periods of
physiological coherence by actively self-generating
positive emotions.
When functioning in a coherent mode, the heart pulls
other biological oscillators into synchronization with
its rhythms, thus leading to entrainment of these
systems (Figure 4.1). Entrainment is an example of a
physiological state in which there is increased coher-
ence between multiple oscillating systems and also
within each system. Thus, our ndings essentially
underscore what people have intuitively known for
some time: Positive emotions not only “feel better,
they actually tend to increase synchronization of
the body’s systems, thereby enhancing energy and
enabling us to function with greater eciency and
effectiveness.
The coherence model takes a dynamic systems ap-
proach that focuses on increasing people’s self-regu-
latory capacity through self-management techniques
that induce a physiological shift, which is reected in
the heart’s rhythms. We also suggest that rhythmic
activity in living systems reects the regulation of
interconnected biological, social and environmental
networks and that important biologically relevant
information is encoded in the dynamic patterns of
physiological activity. For example, information is
encoded in the time interval between action potentials
in the nervous system and patterns in the pulsatile
release of hormones. Our research also suggests
that the time intervals between heartbeats (HRV)
also encode information, which is communicated
across multiple systems and helps synchronize the
system as whole. The afferent pathways from the
heart and blood vessels are given more relevance
in this model because of the signicant degree of
afferent cardiovascular input to the brain and the
consistent generation of dynamic patterns gener-
ated by the heart. Our perspective is that positive
emotions in general, including self-induced positive
emotions, shift the entire system into a more globally
coherent and harmonious physiological mode,
one that is associated with improved system per-
formance, ability to self-regulate and overall well-
being. The coherence model predicts that different
emotions are reected in state-specic patterns in
the heart’s rhythms[5] independent of the amount
of HRV/HR (Figure 4.2). Recent independent work
has veried this by demonstrating a 75% accuracy
rate in detection of discrete emotional states from
the HRV signal using a neural network approach for
pattern recognition.[164] In a study of the effects of
playing violent and nonviolent video games, it was
found that when playing violent video games, the
players had lower cardiac coherence levels and
higher aggression levels than did nonviolent game
27
© Copyright 2015 HeartMath Institute
Chapter 4: Coherence
players and that higher levels of coherence were
negatively related to aggression.[165]
Figure 4.2. Heart-rhythm patterns.
The coherent state has been correlated with a general
sense of well-being and improvements in cognitive,
social and physical performance. We have observed
this association between emotions and heart-rhythm
patterns in studies conducted in both laboratory and
natural settings and for both spontaneous and inten-
tionally generated emotions.[163, 168]
Several studies in healthy subjects, which helped
inform the model, show that during the experience of
positive emotions, a sine-wavelike pattern naturally
emerges in the heart’s rhythms without any conscious
changes in breathing.[51, 133] This is likely because of
more organized outputs of the subcortical structures
involved in processing emotional information, as
described by Pribram,[169] Porges,[82] Oppenheimer
and Hopkins[117] and Thayer,[89] in which the subcor-
tical structures inuence the oscillatory output of
the cardiorespiratory control system in the medulla
oblongata.
A brief summary of the psychophysiological coher-
ence model is provided below. A detailed discussion
on the nature of coherence can be found in two semi-
nal articles.[5, 59]
The Coherence Model Postulates:
1. The functional status of the underlying psycho-
physiological system determines the range of
one’s ability to adapt to challenges, self-regulate
and engage in harmonious social relationships.
Healthy physiological variability, feedback sys-
tems and inhibition are key elements of the com-
plex system for maintaining stability and capacity
to appropriately respond to and adapt to changing
environments and social demands.
2. The oscillatory activity in the heart’s rhythms
reects the status of a network of exible relation-
ships among dynamic interconnected neural struc-
tures in the central and autonomic nervous systems.
3. State-specic emotions are reected in the pat-
terns of the heart’s rhythms independent of
changes in the amount of heart rate variability.
4. Subcortical structures constantly compare infor-
mation from internal and external sensory systems
via a match/mismatch process that evaluates
current inputs against past experience to appraise
the environment for risk or comfort and safety.
5. Physiological or cardiac coherence is reected in
a more ordered sine-wavelike heart-rhythm pattern
associated with increased vagally mediated HRV,
entrainment between respiration, blood pressure
and heart rhythms and increased synchronization
between various rhythms in the EEG and cardiac
cycle.
6. Vagally mediated efferent HRV provides an index
of the cognitive and emotional resources needed
for ecient functioning in challenging environ-
ments in which delayed responding and behavioral
inhibition are critical.
7. Information is encoded in the time between
intervals (action potentials, pulsatile release of
hormones, etc.). The information contained in the
interbeat intervals in the heart’s activity is com-
municated across multiple systems and helps
synchronize the system as a whole.
8. Patterns in the activity of cardiovascular afferent
neuronal trac can signicantly inuence cogni-
tive performance, emotional experience and self-
regulatory capacity via inputs to the thalamus,
amygdala and other subcortical structures.
28
© Copyright 2015 HeartMath Institute
Science of the Heart
9. Increased “rate of change” in cardiac sensory
neurons (transducing BP, rhythm, etc.) during co-
herent states increases vagal afferent neuronal
trac, which inhibits thalamic pain pathways at
the level of the spinal cord.
10. Self-induced positive emotions can shift psycho-
physiological systems into more globally coherent
and harmonious orders that are associated with
improved performance and overall well-being.
The coherence model includes specic approaches
for quantifying the various types of physiological
coherence measures, such as cross-coherence (fre-
quency entrainment between respiration, BP and
heart rhythms), or synchronization among systems
(e.g., synchronization between various EEG rhythms
and the cardiac cycle), autocoherence (stability of a
single waveform such as respiration or HRV patterns)
and system resonance.[5] A coherent heart rhythm is
dened as a relatively harmonic, sine-wavelike signal
with a very narrow, high-amplitude peak in the low-
frequency (LF) region of the HRV power spectrum
with no major peaks in the very-low-frequency (VLF)
or high-frequency (HF) regions. Physiological coher-
ence is assessed by identifying the maximum peak
in the 0.04 to 0.26 hertz range of the HRV power
spectrum, calculating the integral in a window 0.030
hertzwide, centered on the highest peak in that re-
gion and then calculating the total power of the en-
tire spectrum. The coherence ratio is formulated as
(peak power/[total power – peak power]).[5]
Physiological Coherence
A state characterized by:
High heart-rhythm coherence
(sine-wavelike rhythmic pattern).
Increased parasympathetic activity.
Increased entrainment and synchronization
between physiological systems.
Ecient and harmonious functioning of
the cardiovascular, nervous, hormonal and
immune systems.
Social Coherence
Social coherence relates to pairs, family units, groups
or larger organizations in which a network of relation-
ships exists among individuals who share common
interests and objectives. Social coherence is reected
as a stable, harmonious alignment of relationships
that allow for the ecient ow and utilization of en-
ergy and communication required for optimal collec-
tive cohesion and action. There are, of course, cycles
and variations in the quality of family, team or group
coherence, similar to variations in an individual’s
coherence level. Coherence requires that group mem-
bers are attuned and emotionally aligned and that the
group’s energy is globally organized and regulated by
the group as a whole. Group coherence involves the
same principles of global coherence described earlier,
but in this context it refers to the synchronized and
harmonious order in the relationships between and
among the individuals rather than the systems within
the body. The principles, however, remain the same:
In a coherent team, there is freedom for the individual
members to do their part and thrive while maintain-
ing cohesion and resonance within the group’s intent
and goals. Anyone who has watched a championship
sports team or experienced an exceptional concert
knows that something special can happen in groups
that transcends their normal performance. It seems as
though the players are in sync and communicating on
an unseen energetic level. A growing body of evidence
suggests that an energetic eld is formed between
individuals in groups through which communication
among all the group members occurs simultane-
ously. In other words, there is a literal group “eld”
that connects all the members. Sociologist Raymond
Bradley, in collaboration with eminent brain researcher,
neurosurgeon and neuroscientist Dr. Karl Pribram,
developed a general theory of social communication
to explain the patterns of social organization com-
mon to most groups and independent of size, culture,
degree of formal organization, length of existence or
member characteristics. They found that most groups
have a global organization and coherent network of
emotional energetic relations interconnecting virtu-
ally all members into a single multilevel hierarchy.[170]
29
© Copyright 2015 HeartMath Institute
Chapter 5: Establishing A New Baseline
Establishing a New Baseline
At the HMI Research Center, we have found that the heart plays a central role in the generation of emotional
experience and therefore, in the establishment of psychophysiological coherence. From a systems perspec-
tive, the human organism is truly a vast, multidimensional information network of communicating subsystems
in which mental processes, emotions and physiological systems are inextricably intertwined. Whereas our
perceptions and emotions were once believed to be dictated entirely by the brain’s responses to stimuli arising
from our external environment, the emerging perspectives in neuroscience more accurately describe perceptual
and emotional experience as the composite of stimuli the brain receives from the external environment and
the internal sensations or feedback transmitted to the brain from the bodily organs and systems.[5, 79] Thus, the
heart, brain, nervous, hormonal and immune systems must all be considered fundamental components of the
dynamic, interactive information network that determines our ongoing emotional experience.
Extensive work by Pribram has helped advance the
understanding of the emotional system. In Pribram’s
model, past experience builds within us a set of fa-
miliar patterns that are established and maintained
in the neural networks. Inputs to the brain from both
the external and internal environments contribute to
the maintenance of these patterns.
Research has shown that the heart’s afferent neuro-
logical signals directly affect activity in the amygdala
and associated nuclei, an important emotional pro-
cessing center in the brain.[118] The amygdala is the key
brain center that coordinates behavioral, immunologi-
cal and neuroendocrine responses to environmental
threats. It also serves as the processing center for
emotional memory within the brain. In assessing the
external environment, the amygdala scans the inputs
(visual, auditory, smell) for emotional content and
signals and compares them with stored emotional
memories. In this way, the amygdala makes instan-
taneous decisions about the familiarity of incoming
sensory information and because of its extensive con-
nections to the hypothalamus and other autonomic
nervous system centers is able to “hijack” the neural
pathways activating the autonomic nervous system
and emotional response before the higher brain cen-
ters receive the sensory information.[171]
One of the functions of the amygdala is to organize
which patterns become “familiar” to the brain. If the
rhythm patterns generated by the heart are disordered
and incoherent, especially in early life, the amygdala
learns to expect disharmony as the familiar baseline
and thus we feel “at home” with incoherence, which
can affect learning, creativity and emotional balance.
In other words we feel “comfortable” with internal
incoherence, which in this case actually is discom-
fort. On the basis of what has become familiar to the
amygdala, the frontal cortex mediates decisions as
to what constitutes appropriate behavior in any given
situation. Thus, subconscious emotional memories
and associated physiological patterns underlie and
affect our perceptions, emotional reactions, thought
processes and behavior.
________________________________
“Since emotional processes can work faster
than the mind, it takes a power stronger than
the mind to bend perception, override emotional
circuitry, and provide us with intuitive feeling
instead. It takes the power of the heart.
– Doc Childre, HeartMath Institute founder
_________________________________
From our current understanding of the elaborate feed-
back networks between the brain, heart and mental
and emotional systems, it becomes clear that the
CHAPTER 5
30
© Copyright 2015 HeartMath Institute
Science of the Heart
age-old struggle between intellect and emotion will
not be resolved by the mind gaining dominance over
the emotions, but rather by increasing the harmonious
balance between the mental and emotional systems
– a synthesis that provides greater access to our full
range of intelligence.
Within the body, many processes and interactions
occurring at different functional levels provide con-
stant rhythmic inputs with which the brain becomes
familiar. These inputs range from the rhythmic activity
of the heart and our facial expressions, to digestive,
respiratory and reproductive rhythms, to the constant
interplay of messenger molecules produced by the
cells of our body.
These inputs to the brain, translated into neural and
hormonal patterns, are continuously monitored by
the brain and help organize our perception, feelings
and behavior. Familiar input patterns from the exter-
nal environment and from within the body ultimately
are written into neural circuitry and form a stable
backdrop, or reference pattern, against which current
and new information or experiences are compared.
According to this model, when an external or internal
input is suciently different from the familiar refer-
ence pattern, this “mismatch” or departure from the
familiar underlies the generation of emotions.
The background physiological patterns with which
the brain and body grow familiar are created and
reinforced through life experiences and the way we
perceive the world. It’s important to note that the
established patterns may not necessarily be positive
or healthy for a person. For example, someone living
in an environment that continually triggers anger or
feelings of fear is likely to become familiar with these
feelings and their neural and hormonal correlates. In
contrast, an individual whose experience is dominated
by feelings of security, love and care likely will become
familiar with the physiological patterns associated
with these feelings.
In order to maintain stability and feelings of safety
and comfort, we must be able to maintain a match
between our current experience or “reality” and one of
our previously established neural programs.[172] When
we encounter a new experience or challenge, there
can be a mismatch between the input patterns of the
new experience and the lack of a familiar reference.
Depending on the degree of mismatch, it requires
either an internal adjustment (self-regulation) or an
outward behavioral action to reestablish a match and
feeling of comfort. When a mismatch is detected from
either external or internal sensory systems, a change
in activity in the central and autonomic nervous sys-
tems is produced. If the response is short-lived (one
to three seconds), it is called arousal or an orienting
reex. If, however, the stimulus or event is recurrent,
the brain eventually adapts and we habituate by up-
dating the memories that serve as the reference. For
example, people who live in a noisy city adapt to the
ambient noise and eventually tune it out. Subsequent
to this adaptation, it is only when they take a trip to
the quiet countryside that the actual lack of noise
seems strange and is quite noticeable. The mismatch
between the familiar noisy background and the quiet
setting leads to an arousal reaction that gets our at-
tention. It is this departure from the familiar that gives
rise to a signaling function that creates the experience
of an emotion, alerting us to the current state of the
mismatch.
In addition to the monitoring and control processes
for regulation “in the here-and-now,” there are also
appraisal processes that determine the degree of
consistency or inconsistency between a current situ-
ation and the projected future. Appraisals of future
outcomes can be broadly divided into optimistic and
pessimistic.[173] Appraisals that project an inability to
successfully deal with a situation may result in feel-
ings of fear and anxiety. In keeping with the recent
research on attentional bias,[172] this appraisal might
not be accurate because it could be the result of hy-
persensitivity to cues that resemble past traumatic
experiences in the current situation. Alternately, an
inaccurate appraisal can be caused by an instabil-
ity in the neural systems, or a lack of experience or
insight of how to effectively deal with the projected
future situation.[173] Despite the lack of accuracy of the
appraisal, the familiarity of the input can be sucient
to elicit a pessimistic response. This means we can
easily get “stuck” in unhealthy emotional and behav-
31
© Copyright 2015 HeartMath Institute
ioral patterns and lasting improvements in emotional
experience or behaviors cannot be sustained in the
absence of establishing a new set point for the base-
line. If behavior change or improved affective states
are desired, it is therefore critical to focus on strate-
gies that help to establish a new internal reference.
As we successfully navigate new situations or chal-
lenges, the positive experience updates our internal
reference. In essence, we mature through this process
as we learn to more effectively self-regulate our emo-
tions and deal with new situations and challenges. It
is through this process that we are able to develop
a new, healthier internal baseline reference against
which we match inputs so that our assessments of
benign inputs are more accurate and result in feelings
of safety and comfort rather than threat and anxiety.
In a study of high school students who practiced
self-regulation techniques over a four-month period,
their resting HRV was signicantly increased and the
pattern of the HRV was signicantly more coherent
(Figure 5.1). These improvements in resting HRV co-
herence were signicantly correlated with higher test
scores and improved behaviors, suggesting that the
practice of the self-regulation skills induces a more
coherent heart rhythm, reinforcing the association in
the sub-subcortical regulatory systems involved in a
match/mismatch process between more coherent and
stable rhythms in cardiovascular afferent neuronal
trac and feelings we perceive as positive.[110] By
reinforcing this natural coupling in the sub-subcortical
regulatory systems, the self-activation of a positive
feeling can automatically initiate an increase in car-
diac coherence, while at the same time, a physiological
shift resulting from heart-focused breathing can help
facilitate the experience of a positive emotion.
Chapter 5: Establishing A New Baseline
Figure 5.1 Typical resting state heart rate variability patterns in students. HRV recordings from the TestEdge National Demonstration
Study showing examples of two students’ resting-state heart-rhythm patterns, both before and approximately four months after
the TestEdge intervention. Pre- and post-intervention test anxiety level (TAI-Global Scale score) and the CST–English Language
Arts test score for each student are also shown. For the two students in the intervention school, the recordings show a shift
from an erratic, irregular heart-rhythm pattern (left side), before the intervention, to a more coherent pattern (right side), which
indicates the students had established a new more coherent baseline.
[110]
32
© Copyright 2015 HeartMath Institute
Science of the Heart
Self-Regulation and Stability
Pribram and many others have conducted numerous
experiments that provide evidence that the higher
brain centers that monitor the pattern-matching pro-
cess can self-regulate by inhibiting or “gating” the
information owing into the brain.[173] Where we focus
our attention, for example, has a powerful effect on
modulating inputs and thus on determining what gets
processed at higher levels. In a noisy room lled with
many conversations, for instance, we have the ability
to tune out the noise and focus on a single conversa-
tion of interest. In a like manner, we can modulate
pain from a stubbed toe or headache or desensitize
ourselves to sensations like tickling and self-direct
our emotions.[174] Ultimately, when we achieve control
through the process of self-regulation, it results in
feelings of satisfaction and gratication. In contrast,
failure to effectively self-regulate and regain control
often results in feelings of frustration, impatience,
anxiety, overwhelm, hopelessness or depression.
If the neural systems that maintain the baseline
reference patterns are unstable, unsettled emotions
and atypical reactions are likely to be experienced.
These neural systems can be destabilized by trauma,
stress, anxiety or chemical stimulants, to name a few
possibilities. Therefore, it is clear that responding
in healthy and effective ways to ongoing inner and
outer demands and circumstances, such as daily life
situations, depends to a great extent on the synchro-
nization, sensitivity and stability of our physiological
systems.[5, 59]
Neural inputs originate from numerous organs and
muscles, especially in the face. The heart and car-
diovascular system, however, have far more afferent
inputs than other organs and are the primary sources
of consistent dynamic rhythms.[15] In addition to affer-
ent nerve activity associated with mechanical informa-
tion such as pressure and rate that occurs with each
heartbeat, continuous dynamically changing patterns
of afferent activity related to chemical information
is sent to the brain and other systems in the body.
In terms of emotional experience, there are afferent
pathways to the amygdala via the nucleus of tractus
solitarius and the activity in the central nucleus of the
amygdala is synchronized to the cardiac cycle.[10, 177]
Therefore, the afferent inputs from the cardiovascular
system to the amygdala are important contributors in
determining emotional experience and in establishing
the set point to which the current inputs are compared.
In the context of this discussion, it is important to note
that the heart’s rhythmic patterns and the patterns
of afferent neurological signals change to a more or-
dered and stable pattern when one uses HeartMath’s
heart-focused self-regulation techniques. Regular
practice of these techniques, which include a shift
of attentional focus to the center of the chest (heart
area) accompanied by the conscious self-induction
of a calm or positive emotional state, reinforces the
association (pattern match) between a more coher-
ent rhythm and a calm or positive emotion. Positive
feelings then more automatically initiate an increase
in cardiac coherence. Increased coherence initiated
through heart-focused breathing tends to facilitate the
felt experience of a positive emotion. Thus, practice
affects the repatterning process. This is important in
situations where there has been a sustained exposure
to truly high-risk environments or trauma in the past,
but which no longer are in effect and the patterns that
developed in response to them no longer serve the
individual in present safe environments.
Through this feed-forward process, regulatory ca-
pacity is increased and new reference patterns are
established, which the system then strives to main-
tain, making it easier for people to maintain stability
and self-directed control during daily activities, even
in more challenging situations. Without a shift in
the underlying baseline, it is exceedingly dicult to
sustain behavioral change, placing people at risk of
living their lives through the automatic lters of past
familiar experience.
Self-Regulation Techniques that
Reduce Stress and Enhance Human
Performance
With stress levels continuing to rise around the world,
people are becoming more conscious not only of the
long-term effects of stress, but also of how unman-
aged emotions compromise the quality of one’s day-
33
© Copyright 2015 HeartMath Institute
to-day life, limiting mental clarity, productivity, adapt-
ability to life’s challenges and enjoyment of its gifts.
________________________________
“Failures of self-regulation are central to the
vast majority of health and social problems
that plague modern societies.
The most important strength that the majority of
people need to build is the capacity to self-
regulate their emotions, attitudes and behaviors.
– Rollin McCraty
_________________________________
It is commonly believed we have little control over the
mind or emotions. For example, neuroscientist Joseph
LeDoux, who studies brain circuits and the emotion
of fear in animals, writes:
“Emotions are things that happen to us rather than things
we will to occur. Although people set up situations to
modulate their emotions all the time – going to movies
and amusement parks, having a tasty meal, consuming
alcohol and other recreational drugs – in these situations,
external events are simply arranged so that the stimuli
that automatically trigger emotions will be present. We
have little direct control over our emotional reactions.
Anyone who has tried to fake an emotion, or who has been
the recipient of a faked one, knows all too well the futility
of the attempt. While conscious control over emotions is
weak, emotions can flood consciousness.[171], p. 19
While this is true for many people who have not de-
veloped their self-regulation skills, our research and
experience show that the emotional system can be
regulated and brought into coherence. This, of course,
requires practice and effective skills, in much the same
way that it takes techniques and practice to learn and
develop mental or athletic skills.
The research on heart-brain interactions and intu-
ition has informed the development of a set of self-
regulation techniques and practices, the learning of
which can be supported with the use of HRV coher-
ence feedback technologies, collectively known as
the HeartMath System.[178-182] The HeartMath System
offers individuals a systematic and reliable means
Chapter 5: Establishing A New Baseline
to intentionally self-regulate and shift out of a state
of emotional unease or stress into a “new” positive
state of emotional calm and stability. This occurs as
a result of a practice in which an individual intention-
ally activates a positive or calm emotional state as a
future target and activates a shift in patterns of the
heart’s activity to a more coherent state that enables
the person to achieve and maintain stability and emo-
tional composure.
The techniques are designed to enable people to in-
tervene in the moment when negative and disruptive
emotions are triggered, thus interrupting the body’s
normal stress response and initiating a shift toward
increased coherence. This shift facilitates higher
cognitive functioning, intuitive access and increased
emotional regulation, all of which normally are com-
promised during stress and negative emotional states.
The shift in the pattern of the heart’s input to the brain
thus serves to reinforce the self-generated positive
emotional shift, making it easier to sustain. Through
consistent use of HeartMath tools, the coupling be-
tween the psychophysiological coherence mode and
positive emotions is further reinforced.
________________________________
“The emotional frontier is truly the next frontier
to conquer in human understanding.
The opportunity we face now, even before that
frontier is fully explored and settled, is to develop
our emotional potential and accelerate rather
dramatically into a new state of being.
– Doc Childre
_________________________________
Self-Regulation Techniques That
Increase Coherence
There is a paradigm shift emerging on behavioral inter-
vention approaches that teach people self-regulation
strategies that include a physiological aspect such as
HRV biofeedback and that naturally increase vagal
trac. For example, there are many studies showing
that the practice of breathing at 6 breaths per minute,
34
© Copyright 2015 HeartMath Institute
Science of the Heart
supported by HRV biofeedback, induces the coherence
rhythm and has a wide range of benets.[183-189]
In addition to clinical applications, HRV coherence
feedback training often is used to support self-regu-
lation skill acquisition in educational, corporate, law
enforcement and military settings. Several systems
that assess the degree of coherence in the user’s
heart rhythms are available. The majority of these
systems, such as emWave® Pro or Inner Balance® for
iOS devices (HeartMath, Inc.), Relaxing Rhythms (Wild
Divine) and the Stress Resilience Training System
(Ease Interactive), use a noninvasive earlobe or nger
pulse sensor and display the user’s heart rhythm to
provide feedback on the user’s level of coherence.
Emotional self-regulation strategies may contribute
to improved health and performance. Alone or in
combination with HRV coherence biofeedback train-
ing, these strategies have been shown to increase
resilience and accelerate recovery from stressors
and trauma.[53, 58, 81, 190] Self-induced positive emotions
can initiate a shift to increased cardiac coherence
without any conscious intention to change the breath-
ing rhythm.[51, 133] Typically, when people are able to
self-activate a positive or calming feeling rather than
remain focused on their breathing, they enjoy the shift
in feeling and are able to sustain high levels of coher-
ence for much longer time periods.[113]
Heart-focused self-regulation techniques and assis-
tive technologies that provide real-time HRV coher-
ence feedback provide a systematic process for
self-regulating thoughts, emotions, behaviors and
increasing physiological coherence. Many of these
techniques (e.g., HeartMath’s Heart-Focused Breath-
ing, Freeze Frame, Inner Ease and Quick Coherence
techniques[179] are designed to enable people to inter-
vene in the moment they start to experience stress
reactions or unproductive thoughts or emotions. With
practice, one is able to use any of the techniques to
shift into a more coherent physiological state before,
during and after challenging or adverse situations,
thus optimizing mental clarity, emotional composure
and stability.
The rst step in most of the techniques developed
by the HeartMath Institute is called Heart-Focused
Breathing, which includes placing one’s attention in
the center of the chest (the area of the heart) and
imagining the breath is owing in and out of the chest
area while breathing a little slower and deeper than
usual. Conscious regulation of one’s respiration at a
10-second rhythm (ve seconds in and ve seconds
out) (0.1 hertz) increases cardiac coherence and starts
the process of shifting into a more coherent state.[5, 113]
With conscious control over breathing, an individual
can slow the rate and increase the depth of the breath-
ing rhythm. This takes advantage of physiological
mechanisms to modulate efferent vagal activity and
thus the heart rhythm. This increases vagal afferent
nerve trac and increases the coherence (stability) in
the patterns of vagal afferent nerve trac. In turn, this
inuences the neural systems involved in regulating
sympathetic outow, informing emotional experience
and synchronizing neural structures underlying cogni-
tive processes.[5]
In addition to the self-regulation techniques that are
primarily designed to be used in the moment, the
Heart Lock-In Technique is more appropriate when
one has more time to focus on sustaining a coher-
ent state. It enables people to “lock in” the positive
feeling states associated with the heart in order to
boost their energy, heighten peace and clarity and
effectively retrain their physiology to sustain longer
periods of coherent function. With consistent practice,
the Heart Lock-In facilitates the establishment of new
reference patterns promoting increased physiological
eciency, mental acuity and emotional stability as a
new baseline or norm.
While the HeartMath tools are intentionally designed
to be easily learned and used in day-to-day life, our ex-
perience working with people of diverse ages, cultures,
educational backgrounds and professions suggests
that these techniques often facilitate profound shifts
in perception, emotion and awareness. Moreover,
extensive laboratory research performed at HMI has
shown that the physiological changes accompanying
such shifts are dramatic.
35
© Copyright 2015 HeartMath Institute
Several studies using various combinations of these
self-regulation techniques have found signicant cor-
relations between HRV coherence and improvements
in cognitive function and self-regulatory capacity.
For example:
> A study of middle school students with attention-
deficit hyperactivity disorder showed a wide
range of signicant improvements in short- and
long-term memory, ability to focus and signicant
improvements in behaviors both at home and in
school.[108]
> A study of 41 ghter pilots engaging in ight simu-
lator tasks found a signicant correlation between
higher levels of performance and heart-rhythm
coherence as well as lower levels of frustration.[189]
> A study of recently returning soldiers from Iraq who
were diagnosed with PTSD found that relatively
brief periods of HRV coherence training combined
with practicing the Quick Coherence Technique re-
sulted in signicant improvements in the ability to
self-regulate along with a wide range of cognitive
functions. The degree of improvement correlated
with increased cardiac coherence.[109]
> Other studies have shown increases in parasym-
pathetic activity (vagal tone),[133] reductions in
cortisol and increases in DHEA,[116] decreases in
blood pressure and stress measures in hyper-
tensive populations,[113, 115] reduced health-care
costs[112] and signicant improvements in the
functional capacity of patients with congestive
heart failure.[192]
> A study of correctional ocers showed reductions
in systolic and diastolic BP, total cholesterol, fast-
ing glucose, overall stress, anger, fatigue and hos-
tility.[114] Similar results were obtained in several
studies with police ocers.[53, 193]
In addition to the emotional self-regulation techniques,
there are other approaches that also increase HRV
coherence. For example, a study of Zen monks found
that monks with greater experience in meditation
Chapter 5: Establishing A New Baseline
tended to have more coherent heart rhythms dur-
ing their resting recording than those who had been
monks for less than two years.[194] A study of auto-
genic training showed increased HRV coherence and
found that cardiac coherence was strongly correlated
with EEG alpha activity. The authors suggested that
cardiac coherence could be a general marker for the
meditative state.[195] However, this does not suggest
that all meditation or prayer styles increase coher-
ence, unless the coherence state is driven by a focus
on breathing at a 10-second rhythm or the activation
of a positive emotion.[196-199] For example, a study
examining HRV while reciting rosary or bead prayers
and yoga mantras found that a coherent rhythm was
produced by rhythmically breathing, but not by random
verbalization or breathing. The authors ascribed the
mechanisms for this nding to a breathing pattern of
6-cycles per minute.[200] In a study of the effects of ve
types of prayer on HRV, it was found that all types of
prayer elicited increased cardiac coherence. However,
prayers of gratefulness and heartfelt love resulted in
denitively higher coherence levels.[201] It also has been
shown that tensing the large muscles in the legs in a
rhythmical manner at a 10-second rhythm can induce
a coherent heart rhythm.[202]
36
© Copyright 2015 HeartMath Institute
Science of the Heart
Energetic Communication
The rst biomagnetic signal was demonstrated in 1863 by Gerhard Baule and Richard McFee in a magneto-
cardiogram (MCG) that used magnetic induction coils to detect elds generated by the human heart.[203] A
remarkable increase in the sensitivity of biomagnetic measurements has since been achieved with the introduc-
tion of the superconducting quantum interference device (SQUID) in the early 1970s. The ECG and MCG signals
have since been shown to closely parallel one another.[204]
In this section, we discuss how the magnetic elds
produced by the heart are involved in energetic com-
munication, which we also refer to as cardioelectro-
magnetic communication. The heart is the most pow-
erful source of electromagnetic energy in the human
body, producing the largest rhythmic electromagnetic
eld of any of the body’s organs. The heart’s electrical
eld is about 60 times greater in amplitude than the
electrical activity generated by the brain. This eld,
measured in the form of an electrocardiogram (ECG),
can be detected anywhere on the surface of the body.
Furthermore, the magnetic eld produced by the heart
is more than 100 times greater in strength than the
eld generated by the brain and can be detected up
to 3 feet away from the body, in all directions, using
SQUID-based magnetometers (Figure 6.1).
Figure 6.1.The heart’s magnetic eld, which is the strongest
rhythmic eld produced by the human body, not only envelops
every cell of the body, but also extends out in all directions
into the space around us. The heart’s magnetic eld can
be measured several feet away from the body by sensitive
magnetometers. Research conducted at HMI suggests the
heart’s eld is an important carrier of information.
Prompted by our ndings that the timing between
pulses of the heart’s magnetic eld is modulated by
different emotional states, we have performed several
studies that show the magnetic signals generated
by the heart have the capacity to affect individuals
around us.
Biological Encoding of Information
Every cell in our bodies is bathed in an external and
internal environment of uctuating invisible magnetic
forces.[205] It has become increasingly apparent that
uctuations in magnetic elds can affect virtually ev-
ery circuit in biological systems to a greater or lesser
degree, depending on the particular biological system
and the properties of the magnetic uctuations.[5, 205]
One of the primary ways that signals and messages
are encoded and transmitted in physiological systems
is in the language of patterns. In the nervous system it
is well established that information is encoded in the
time intervals between action potentials, or patterns
of electrical activity.[206] This also applies to humoral
communications in which biologically relevant infor-
mation also is encoded in the time interval between
hormonal pulses.[207-209] As the heart secretes a number
of different hormones with each contraction, there is
a hormonal pulse pattern that correlates with heart
rhythms. In addition to the encoding of information in
the space between nerve impulses and in the intervals
between hormonal pulses, it is likely that information
also is encoded in the interbeat intervals of the pres-
sure and electromagnetic waves produced by the
heart. This supports Pribram’s proposal discussed
earlier that low-frequency oscillations generated by
the heart and body in the form of afferent neural,
CHAPTER 6
37
© Copyright 2015 HeartMath Institute
hormonal and electrical patterns are the carriers
of emotional information and the higher frequency
oscillations found in the EEG reect the conscious
perception and labeling of feelings and emotions.[169]
We have proposed that these same rhythmic patterns
also can transmit emotional information via the elec-
tromagnetic eld into the environment, which can be
detected by others and processed in the same manner
as internally generated signals.
Heartbeat-Evoked Potentials
A useful technique for detecting synchronized activity
between systems in biological systems and investigat-
ing a number of bioelectromagnetic phenomena is sig-
nal averaging. This is accomplished by superimposing
any number of equal-length epochs, each of which
contains a repeating periodic signal. This emphasizes
and distinguishes any signal that is time-locked to the
periodic signal while eliminating variations that are
not time-locked to the periodic signal. This procedure
is commonly used to detect and record cerebral corti-
cal responses to sensory stimulation [210]. When signal
averaging is used to detect activity in the EEG that
is time-locked to the ECG, the resultant waveform is
called the heartbeat-evoked potential.
The heart generates a pressure wave that travels
rapidly throughout the arteries, much faster than the
actual ow of blood that we feel as our pulse. These
pressure waves force the blood cells through the
capillaries to provide oxygen and nutrients to cells
and expand the arteries, causing them to generate
a relatively large electrical voltage. These pressure
waves also apply pressure to the cells in a rhythmic
fashion that can cause some of their proteins to gener-
ate an electrical current in response to this “squeeze.
Experiments conducted in our laboratory have shown
that a change in the brain’s electrical activity can be
seen when the blood-pressure wave reaches the brain
around 240 milliseconds after systole.
Chapter 6: Energetic Communication
Figure 6.2. Heartbeat-evoked potentials. This gure shows an example of typical heartbeat-evoked potentials. In this example,
450 averages were used. The pulse wave also is shown, indicating the timing relationship of the blood-pressure wave reaching
the brain. In this example, there is less synchronized alpha activity immediately after the R-wave. The time range between 10 and
240 milliseconds is when afferent signals from the heart are impinging upon the brain and the alpha desynchronization indicates
the processing of this information. Increased alpha activity can be seen later in the waveforms, starting at around the time the
blood-pressure wave reaches the brain.
38
© Copyright 2015 HeartMath Institute
Science of the Heart
There is a replicable and complex distribution of
heartbeat-evoked potentials across the scalp.
Changes in these evoked potentials associated with
the heart’s afferent neurological input to the brain are
detectable between 50 to 550 milliseconds after the
heartbeat.[8] Gary Schwartz and his colleagues at the
University of Arizona believe the earlier components in
this complex distribution cannot be explained by sim-
ple physiological mechanisms alone and suggest that
an energetic interaction between the heart and brain
also occurs.[211] They have conrmed our ndings that
heart-focused attention is associated with increased
heart-brain synchrony, providing further support for
energetic heart-brain communications.[5] Schwartz
and his colleagues also demonstrated that when
subjects focused their attention on the perception of
their heartbeat, the synchrony in the preventricular
region of the heartbeat-evoked potential increased.
They concluded that this synchrony may reect an
energetic mechanism of heart-brain communication,
while post-ventricular synchrony most likely reects
direct physiological mechanisms.
Biomagnetic Communication Between
People
We have found there is a direct relationship between
the heart-rhythm patterns and the spectral informa-
tion encoded in the frequency spectra of the magnetic
eld radiated by the heart. Thus, information about
a person’s emotional state is encoded in the heart’s
magnetic eld and is communicated throughout the
body and into the external environment.
Figure 6.3 shows two different power spectra derived
from an average of 12 individual 10-second epochs of
ECG data recorded during differing psychophysiologi-
cal modes. The plot on the left was produced while the
subject was in a state of deep appreciation, whereas
the plot on the right was generated while the subject
experienced recalled feelings of anger. The difference
in the patterns and thus the information they contain,
can be seen clearly. There is a direct correlation be-
tween the patterns in the heart rate variability rhythm
and the frequency patterns in the spectrum of the
ECG or MCG. Experiments such as these indicate that
psychophysiological information can be encoded into
the electromagnetic elds produced by the heart.[163, 212]
Figure 6.3. ECG spectra during different emotional states.
The above graphs are the average power spectra of 12
individual 10-second epochs of ECG data, which reflect
information patterns contained in the electromagnetic eld
radiated by the heart. The left-hand graph is an example of
a spectrum obtained during a period of high heart-rhythm
coherence generated during a sustained heartfelt experience
of appreciation. The graph on the right depicts a spectrum
associated with a disordered heart rhythm generated during
feelings of anger.
The human body is replete with mechanisms for
detecting its external environment. Sense organs,
the most obvious example, are specically geared
to react to touch, temperature, select ranges of light,
sound waves, etc. These organs are acutely sensitive
to external stimuli. The nose, for example, can detect
one molecule of gas, while a cell in the retina of the
eye can detect a single photon of light. If the ear were
any more sensitive, it would pick up the sound of the
random vibrations of its own molecules.[213]
The interaction between two human beings, such as,
the consultation between patient and clinician or a
discussion between friends, is a very sophisticated
dance that involves many subtle factors. Most people
tend to think of communication solely in terms of overt
signals expressed through facial movements, voice
qualities, gestures and body movements. However,
evidence now supports the perspective that a subtle
yet inuential electromagnetic or “energetic” com-
munication system operates just below our conscious
level of awareness. The following section will discuss
data that suggests this energetic system contributes
to the “magnetic” attractions or repulsions that occur
between individuals.
39
© Copyright 2015 HeartMath Institute
The ability to sense what other people are feeling is
an important factor in allowing us to connect, or com-
municate effectively with them. The smoothness or
ow in any social interaction depends to a great extent
on the establishment of a spontaneous entrainment
or linkage between individuals. When people are
engaged in deep conversation, they begin to fall into
a subtle dance, synchronizing their movements and
postures, vocal pitch, speaking rates and length of
pauses between responses,[214] and, as we are now
discovering, important aspects of their physiology
also can become linked and synchronized.
The Electricity of Touch:
Detection and Measurement of Cardiac
Energy Exchange Between People
An important step in testing our hypothesis that the
heart’s electromagnetic eld could transmit signals
between people was to determine if an individual’s
eld and the information modulated within it could be
detected by others. In conducting these experiments,
the question being asked was straightforward: Can
the electromagnetic eld generated by the heart of
one individual be detected in physiologically relevant
ways in another person, and if so, does it have any
discernible biological effects? To investigate these
possibilities, we used signal-averaging techniques to
detect signals that were synchronous with the peak
of the R-wave of one subject’s ECG in recordings of
another subject’s electroencephalogram (EEG) or
brain waves. My colleagues and I have performed
numerous experiments in our laboratory over several
years using these techniques.[215] Several examples are
included below to illustrate some of our ndings. In the
majority of these experiments, subjects were seated
in comfortable, high-back chairs to minimize postural
changes with the positive ECG electrode located on
the side at the left sixth rib and referenced to the right
supraclavicular fossa, according to the International
10-20 system. The ECG and EEG were recorded for
both subjects simultaneously so the data (typically
sampled at 256 hertz or higher) could be analyzed
for simultaneous signal detection in both (Figure 6.4).
To clarify the direction in which the signal ow was
analyzed, the subject whose ECG R-wave was used as
the time reference for the signal-averaging procedure
is referred to as the “signal source,” or simply “source.
The subject whose EEG was analyzed for the registra-
tion of the source’s ECG signal is referred to as the
signal receiver,” or simply “receiver.” The number of
averages used in the majority of the experiments was
250 ECG cycles (~4 minutes). The subjects did not
consciously intend to send or receive a signal and,
in most cases, were unaware of the true purpose of
the experiments. The results of these experiments
have led us to conclude that the nervous system
acts as an antenna, which is tuned to and responds
to the magnetic fields produced by the hearts of
other individuals. My colleagues and I call this ener-
getic information exchange energetic communication
and believe it to be an innate ability that heightens
awareness and mediates important aspects of true
empathy and sensitivity to others. Furthermore, we
have observed that this energetic communication
ability can be enhanced, resulting in a much deeper
level of nonverbal communication, understanding
and connection between people. We also propose
that this type of energetic communication between
individuals may play a role in therapeutic interactions
between clinicians and patients that has the potential
to promote the healing process.
From an electrophysiological perspective, it appears
that sensitivity to this form of energetic communica-
tion between individuals is related to the ability to be
emotionally and physiologically coherent. The data
indicate that when individuals are in the coherent
state, they are more sensitive to receiving information
contained in the magnetic elds generated by others.
In addition, during physiological coherence, internal
systems are more stable, function more eciently
and radiate electromagnetic elds containing a more
coherent structure.[163]
The rst step was to determine if the ECG signal of
one person could be detected in another individual’s
EEG during physical contact. For these experiments,
we seated pairs of subjects 4 feet apart and monitored
them simultaneously.
Chapter 6: Energetic Communication
40
© Copyright 2015 HeartMath Institute
Science of the Heart
Although in most pairs a clear signal transfer between
the two subjects was measurable in one direction, it
was only observed in both directions simultaneously
in about 30 percent of the pairs (i.e., Subject 2’s ECG
could be detected in Subject 1’s EEG at the same time
Subject 1’s ECG was detectable in Subject 2’s EEG).
As shown later, an important variable appears to be
the degree of physiological coherence maintained.
After demonstrating that the heart’s activity could be
detected in another’s EEG during physical contact, we
completed a series of experiments to determine if the
signal was transferred via electrical conduction alone
or if it also was energetically transferred via magnetic
elds. The results suggest a signicant degree of
signal transfer occurs through skin conduction, but
it also is radiated between individuals, which will be
discussed next.
Figure 6.4. Heartbeat signal-averaged waveforms showing a
transference of the electrical energy generated by Subject B’s
heart can be detected in Subject A’s EEG (brain waves) when
they hold hands.
Heart-Brain Synchronization During
Nonphysical Contact
Because the magnetic component of the eld pro-
duced by the heartbeat naturally radiates outside
the body and can be detected several feet away with
SQUID-based magnetometers,[217] we decided to further
test the transference of signals between subjects who
were not in physical contact. In these experiments,
the subjects either were seated side by side or fac-
ing each other at varying distances. In some cases,
we were able to detect a clear QRS-shaped signal
in the receiver’s EEG. Although the ability to obtain
a clear registration of the ECG in the other person’s
EEG declined as the distance between subjects was
increased, the phenomenon appears to be nonlinear.
For instance, a clear signal could be detected at a
distance of 18 inches in one session, but was unde-
tectable in the very next trial at a distance of only 6
inches. Although transmission of a clear QRS-shaped
signal is uncommon at distances over 6 inches in
our experience, physiologically relevant information
is communicated between people at much further
distances and is reected in synchronized activity.
Figure 6.5 shows the data from two subjects seated
and facing one another at a distance of 5 feet, with no
physical contact. They were asked to use the Heart
Lock-In Technique,[179] which has been shown to pro-
duce sustained states of physiological coherence.[116]
Participants were not aware of the purpose of the
experiment. The top three traces show the signal-
averaged waveforms derived from the EEG locations
along the medial line of the head.
Figure 6.5. Heart-brain synchronization between two people.
The top three traces are Subject 2’s signal-averaged EEG
waveforms, which are synchronized to the R-wave of Subject
1’s ECG. The lower plot shows Subject 2’s heart rate variability
pattern, which was coherent throughout the majority of the
record. The two subjects were seated at a conversational
distance without physical contact.
41
© Copyright 2015 HeartMath Institute
Note that in this example the signal-averaged wave-
forms do not contain any semblance of the QRS
complex shape as seen in the physical contact ex-
periments. Rather, they reveal the occurrence of an
alpha-wave synchronization in the EEG of one subject
that is precisely timed to the R-wave of the other
subject’s ECG.
Power-spectrum analysis of the signal-averaged
EEG waveforms showed that the alpha rhythm was
synchronized to the other person’s heart. This alpha
synchronization does not imply that there is increased
alpha activity, but it does show that the existing alpha
rhythm is able to synchronize to extremely weak exter-
nal electromagnetic elds such as those produced by
another person’s heart. It is well known that the alpha
rhythm can synchronize to an external stimulus such
as sound or light ashes, but the ability to synchronize
to such a subtle electromagnetic signal is surprising.
As mentioned, there also is a signicant ratio of alpha
activity that is synchronized to one’s own heartbeat
and the amount of this synchronized alpha activity is
signicantly increased during periods of physiological
coherence.[5, 219]
Figure 6.6 shows an overlay plot of one of Subject 2’s
signal-averaged EEG traces and Subject 1’s signal-
averaged ECG.
Figure 6.6. Overlay of signal-averaged EEG and ECG. This
graph is an overlay plot of the same EEG and ECG data shown
in Figure 6.5. Note the similarity of the wave shapes, indicating
a high degree of synchronization.
This view shows an amazing degree of synchroniza-
tion between the EEG of Subject 2 and Subject 1’s
heart. These data show it is possible for the magnetic
signals radiated by the heart of one individual to inu-
ence the brain rhythms of another. In addition, this
phenomenon can occur at conversational distances.
Energetic Sensitivity and Empathy
Figure 6.7 shows the data from the same two sub-
jects during the same time period, but it is analyzed
for alpha synchronization in the opposite direction
(Subject 1’s EEG and Subject 2’s ECG). In this case,
we see that there is no observable synchronization
between Subject 1’s EEG and Subject 2’s ECG. The
key difference between the data shown in gures 6.5
and 6.6 is the high degree of physiological coherence
maintained by Subject 2. In other words, the degree of
coherence in the receiver’s heart rhythms appears to
determine whether his/her brain waves synchronize
to the other person’s heart.
Figure 6.7. The top three traces are the signal-averaged EEG
waveforms for Subject 1. There is no apparent synchronization
of Subject 1’s alpha rhythm to Subject 2’s ECG. The bottom
plot is a sample of Subject 1’s heart rate variability pattern,
which was incoherent throughout the majority of the record.
This suggests that when a person is in a physio-
logically coherent state, he or she exhibits greater
sensitivity in registering the electromagnetic signals
Chapter 6: Energetic Communication
42
© Copyright 2015 HeartMath Institute
Science of the Heart
and information patterns encoded in the elds radi-
ated by others’ hearts. At rst glance the data may
be interpreted to mean we are more vulnerable to the
potential negative inuence of incoherent patterns
radiated by those around us. In fact, the opposite is
true. When people are able to maintain the physiologi-
cal coherence mode, they are more internally stable
and thus less vulnerable to being negatively affected
by the elds emanating from others. It appears that
increased internal stability and coherence is what al-
lows the increased sensitivity to emerge.
This ts quite well with our experience in training
thousands of individuals how to self-generate and
maintain coherence while they are communicating
with others. Once individuals learn this skill, it is a
common experience that they become much more
attuned to other people and are able to detect and
understand the deeper meaning behind spoken words.
They often are able to sense what someone else truly
wishes to communicate even when the other person
may not be clear in what he or she is attempting to
say. The Coherent Communication Technique helps
people to feel fully heard, speak authentically and
with discernment and promote greater rapport and
empathy between people.[180]
Heart-Rhythm Synchronization Between
People
When heart rhythms are more coherent, the elec-
tromagnetic eld that is radiated outside the body
correspondingly becomes more organized, as shown
in Figure 6.3. The data presented thus far indicate
that signals and information can be communicated
energetically between individuals and that they have
measurable biological effects, but so far have not
implied a literal synchronization of two individuals’
heart-rhythm patterns. We have found that synchro-
nization of heart-rhythm patterns between individuals
is possible, but usually occurs only under specic
conditions. In our experience, true heart-rhythm syn-
chronization between individuals is rare during normal
waking states. We have found that individuals who
have a close working or living relationship are the best
candidates for exhibiting true heart-rhythm synchroni-
zation. Figure 6.8 shows an example of heart-rhythm
synchronization between two women who have a
close working relationship and practice coherence-
building techniques regularly. For this experiment,
they were seated 4 feet apart and were consciously
focused on generating feelings of appreciation for
each other.
Figure 6.8. Heart-rhythm entrainment between two people.
These data were recorded while both subjects were practicing
the Heart Lock-In Technique and consciously feeling
appreciation for each other.
A more complex type of synchronization also can
occur during sleep. Although we have only looked at
couples who are in long-term stable and loving rela-
tionships, we have been surprised at the high degree
of heart-rhythm synchrony observed in these couples
while they sleep. Figure 6.9 shows an example of a
small segment of data from one couple.
Figure 6.9. Heart-rhythm entrainment between husband and
wife during sleep.
These data were recorded using an ambulatory ECG re-
corder with a modied cable harness that allowed the
concurrent recording of two individuals on the same
recording. Note how the heart rhythms simultaneously
change in the same direction and how heart rates
converge. Throughout the recording, clear transition
43
© Copyright 2015 HeartMath Institute
periods are evident in which the heart rhythms move
into greater synchronicity for some time and then drift
out again. This implies that unlike in most wakeful
states, synchronization between the heart rhythms of
individuals can and does occur during sleep.
Another line of research that has shown physiological
synchronization between people was in a study of a
30-minute Spanish rewalking ritual. Heart-rate data
was obtained from 38 participants and synchronized
activity was compared between firewalkers and
spectators. They showed ne-grained commonalities
of arousal during the ritual between rewalkers and
related spectators but not unrelated spectators. The
authors concluded that their ndings demonstrated
that a collective ritual can evoke synchronized arousal
over time between active participants and relatives
or close friends. They also suggest that the study
links eld observations to a physiological basis and
offers a unique approach for the quantication of
social effects on human physiology during real-world
interactions, a mediating mechanism that is likely
informational.[220]
Morris[221] studied the effect of heart coherence in a
group setting with participants who were trained in
HeartMath’s Quick Coherence® Technique. He con-
ducted 148 10-minute trials in which three trained
participants were seated around a table with one
untrained participant. During each trial, three of
the trained participants were placed with untrained
volunteers to determine whether the three could col-
lectively facilitate higher levels of HRV coherence
in the untrained individual. The coherence of the
HRV of the untrained subject was found to be higher
in approximately half of all matched comparisons
when the trained participants focused on achieving
increased coherence. In addition, evidence of heart-
rhythm synchronization between group participants
was revealed through several evaluation methods and
higher levels of coherence correlated to higher levels
of synchronization between participants. There was
a statistical relationship between this synchroniza-
tion and relational measures (bonding) among the
participants. The authors concluded that “evidence
of heart-to-heart synchronization across subjects was
Chapter 6: Energetic Communication
found, lending credence to the possibility of heart-to-
heart biocommunications.
Using signal-averaging techniques, we also were able
to detect synchronization between a mother’s brain
waves (EEG-CZ) and her baby’s heartbeats (ECG).
The pair were not in physical contact, but when the
mother focused her attention on the baby, her brain
waves synchronized to the baby’s heartbeats (Figure
6.10). We were not able to detect that the infant’s EEG
synchronized to the mother’s heartbeats.
Figure 6.10. ECG and EEG synchronization between mother
and baby.
Biomagnetic Communication Between
People and Animals
Farmers and attentive observers know that most
cattle and sheep, when grazing, face the same way.
It has been demonstrated by means of satellite im-
ages, eld observations and measurements of deer
beds in snow that domestic cattle across the globe
and grazing and resting red and roe deer align their
body axes in roughly a north-south direction and ori-
ent their heads northward when grazing or resting.
Wind and light conditions were excluded as common
determining factors, so magnetic alignment with the
earth’s geomagnetic eld was determined to be the
best explanation. Magnetic north was a better predic-
tor than geographic north, suggesting large mammals
have magnetoreception capability.[222]
44
© Copyright 2015 HeartMath Institute
Science of the Heart
We also have found that a type of heart-rhythm syn-
chronization can occur in interactions between people
and their pets. Figure 6.11 shows the results of an
experiment looking at the heart rhythms of my son,
Josh (age 12 at the time of the recording) and his dog,
Mabel. Here we used two Holter recorders, one tted
on Mabel and the other on Josh. We synchronized the
recorders and placed Mabel in one of our labs.
Josh entered the room and sat down and proceeded
to do a Heart Lock-In and consciously radiate feelings
of love toward Mabel. There was no physical contact
and he did not make any attempts to get the dog’s at-
tention. In Figure 6.11, note the synchronous shift to
increased coherence in the heart rhythms of both Josh
and Mabel as Josh consciously feels love for his pet.
Another example of an animal’s heart-rhythm pattern
shifting in response to a human’s shift of emotional
states is shown in Figure 6.12. This was a collabora-
tive study with Ellen Gehrke, Ph.D. who consciously
shifted into a coherent state while sitting in a corral
with her horse, neither touching nor petting it. When
she shifted into a coherent state, the horse’s heart-
rhythm pattern also shifted to a more ordered pattern.
In other trials, very similar shifts in horses’ HRV pat-
terns were seen in three out of four horses’ heart
rhythms. One of the horses that did not show any
response was well known for not relating well to hu-
mans or other horses.
Figure 6.11. Heart-rhythm
patterns of a boy and his dog.
These data were obtained using
ambulatory ECG recorders tted
on both Josh, a young boy and
Mabel, his pet dog. When Josh
entered the room where Mabel
was waiting and consciously felt
feelings of love and care towards
his pet, his heart rhythms became
more coherent and this change
appears to have inuenced Mabel
heart rhythms, which shifted to a
more coherent rhythm.
Figure 6.12. Heart-rhythm
patterns of woman and horse.
These data were obtained using
ambulatory ECG recorders tted
on both Ellen and her horse,
Tonopah. When she did a Heart
Lock-In, her heart rhythms
became more coherent and
this change appears to have
influenced the horse’s heart
rhythms.
45
© Copyright 2015 HeartMath Institute
Intuition Research:
Coherence and the Surprising Role of the Heart
In a world whose pace and complexity is ever increasing, where we face more and more personal and social
challenges, there is a call for lifting individual and global consciousness. People want to make more intelligent
choices so daily life is more tenable, personal and global relationships are stronger and more meaningful and
the future of our planet is assured.[223]
Raising individual and global consciousness can help
us improve personal and collective health, well-being
and harmony. We suggest that this begins with people
taking greater responsibility for their day-to-day de-
cisions, actions and behaviors, which can result in
establishing a new and healthier physiological and
psychological internal baseline reference. Establish-
ing a baseline requires having effective and practical
strategies available for handling daily situations,
making good decisions and taking meaningful and
appropriate action.
Much attention has been given to identifying the
many factors that go into making good decisions.
Among these are awareness of self and others, cogni-
tive exibility and self-regulation of emotions. All of
these are important for bringing more consciousness
into our daily situations and the decisions we make.
Something else that should be considered in good de-
cision-making – and we’ve all experienced it, perhaps
without being fully aware of it – is intuition. There is
fascinating research that is beginning to uncover the
nature and function of intuition, or what researchers
refer to as intuitive intelligence. In a literature review
of intuition, Gerard Hodgkinson of Leeds University in
England notes that despite the many conceptualiza-
tions of intuition, there is a growing body of research
suggesting there are underlying nonconscious as-
pects of intuition. Among the nonconscious aspects
of intuition which are involved in intuitive perception
are implicit learning, or implicit knowledge.[224] It is
commonly acknowledged that intuitive perception
plays an important role in business decisions and
entrepreneurship, learning, medical diagnosis, healing,
spiritual growth and overall well-being.[225, 226]
Chapter 7: Intuition Research: Coherence and the Surprising Role of the Heart
Research also suggests intuition may play an im-
portant role in social cognition, decision-making and
creativity. When addressing life situations, people
often default to familiar patterns of thoughts, feelings
and actions in both the decision-making process and
how they see others.
Rather than responding to situations from habitual
patterns that are not necessarily healthy or con-
structive, those situations could be more effectively
addressed with new and creative solutions. These
solutions can take into consideration the available
inner resources that are congruent with one’s deeper
intuition and core values. In other words, we can learn
to intentionally align with and access our intuitive
intelligence, which can provide moment-to-moment
guidance and empower what HeartMath calls heart-
based living, reliance in all things on the wisdom,
intelligence and qualities of the heart.
The origin of the word “intuition” is the Latin verb
intueri, which is usually translated as to look inside
or to contemplate. Hodgkinson concludes that “in-
tuiting” is a complex set of interrelated cognitive,
affective and somatic processes in which there is no
apparent intrusion of deliberate, rational thought. He
also concludes that the considerable body of theory
and research that has emerged in recent years dem-
onstrates that the concept of intuition has emerged
as a legitimate subject of scientic inquiry that has
important ramications for educational, personal,
medical and organizational decision-making, per-
sonnel selection and assessment, team dynamics,
training and organizational development.[224] Another
comprehensive review of intuition literature yielded
CHAPTER 7
46
© Copyright 2015 HeartMath Institute
Science of the Heart
this denition of intuition: “Affectively charged judg-
ments that arise through rapid, nonconscious and
holistic associations.[227]
Several researchers have contended that intuition is
an innate ability that all humans possess in one form
or another and is arguably the most universal natural
ability we possess. They also say the ability to intuit
could be regarded as an inherited unlearned gift.[228,
229] A common element also found in most discus-
sions and denitions of intuition is that of affect or
emotions. Although intuitions are felt, they can be
accompanied by cognitive content and perception of
information. Our research and experience suggests
that emotions are the primary language of intuition
and that intuition offers a largely untapped resource
to manage and uplift our emotions, daily experience
and consciousness.
Types of Intuition
Our research at the HeartMath Institute suggests there
are three categories or types of processes the word
intuition describes. The rst type of intuition, often
called implicit knowledge or implicit learning, essen-
tially refers to knowledge we’ve acquired in the past
and either forgot or did not realize we had learned.
Drawing on the neuroscience conception of the hu-
man brain as a highly ecient and effective pattern-
matching device,[176] a number of pattern-recognition
models have been developed to show how this fast
type of intuitive decision-making and action can be
understood purely in terms of neural processes. In
this regard, the brain matches the patterns of new
problems or challenges with implicit memories based
on prior experience.[224, 230, 231]
The second type of intuition is what we call energetic
sensitivity, which refers to the ability of the nervous
system to detect and respond to environmental sig-
nals such as electromagnetic elds (also see Ener-
getic Communication section). It is well established
that in both humans and animals, nervous-system
activity is affected by geomagnetic activity.[232] Some
people, for example, appear to have the capacity to feel
or sense that an earthquake is about to occur before
it happens. It has recently been shown that changes
in the earth’s magnetic eld can be detected about an
hour or even longer before a large earthquake occurs.
[231] Another example of energetic sensitivity is the
sense of being stared at. Several scientic studies
have veried this type of sensitivity.[234]
The third type of intuition is nonlocal intuition, which
refers to the knowledge or sense of something that
cannot be explained by past or forgotten knowledge
or by sensing environmental signals. It has been
suggested that the capacity to receive and process
information about nonlocal events appears to be a
property of all physical and biological organization
and this likely is because of an inherent interconnect-
edness of everything in the universe.[235-237] Examples
of nonlocal intuition include when a parent senses
something is happening to his or her child who is
many miles away, or the repeated, successful sensing
experienced by entrepreneurs about factors related to
making effective business decisions.
Figure 7.1. The three types of intuition
Implicit Learning
The question of how intuition interacts with deliber-
ate, conscious thought processes, has long been the
subject of debate. Research in the elds of cognitive
and social psychology has produced the commonly
accepted dual-process theory, which suggests there
are two separate processing systems. The rst system
is unconscious, automatic and intuitive. It processes
information very rapidly and associates current inputs
47
© Copyright 2015 HeartMath Institute
to the brain with past experiences. Therefore, it is rela-
tively undemanding in its use of cognitive resources.
For example, when individuals have gained experience
in a particular eld, implicit intuitions are derived from
their capacity to recognize important environmental
cues and rapidly and unconsciously match those
cues to existing familiar patterns. This results in
rapid and effective diagnosis or problem-solving. In
contrast, the second processing system is conscious
in nature, relatively slow, rule-based and analytic. It
places greater demands on cognitive resources than
the rst system.[224]
Insight
The term intuition also is used commonly to describe
experiences scientic literature refers to as insight.
When we have a problem we cannot immediately solve,
the brain can be working on it subconsciously. It is
common when we are in the shower, driving or doing
something else and not thinking about the problem that
a solution pops into the conscious mind, a process we
experience as an intuitive insight. This type of implicit
process involves a longer gestation period following an
impasse in problem-solving before a sudden insight-
ful perception or strategy that leads to a solution.[238]
In contrast, intuition in the dual-processing models
of implicit intuition described above occurs almost
instantaneously and is emotionally charged.[239]
Nonlocal Intuition
The study of nonlocal intuition, which at times has
been thought of as being in the same category as
telepathy, clairvoyance and precognition, has been
fraught with debate in the scientic community.[240]
While there are various theories that attempt to explain
how the process of intuition functions, these theories
have yet to be conrmed, so an integrated theory re-
mains to be formulated. Nevertheless, there is now a
large body of documented rigorous scientic research
on nonlocal intuitive perception that dates back more
than seven decades. A variety of experiments show it
cannot be explained by aws in experimental design
or research methods, statistical techniques, chance
or selective reporting of results.[239]
A meta-analysis of nine experiments that measured
physiological responses occurring before a future
event (pre-stimulus responses) that could not oth-
erwise be anticipated through any known inferential
process, revealed statistically signicant results in
eight of the nine studies in over 1,000 subjects.[240] Sub-
sequent to this, a researcher, by examining 26 studies,
also concluded that a clear pre-stimulus response in
physiological activity occurred before unpredictable
stimuli, despite the fact there is not yet any known
explanation of the mechanisms for this nding.[242]
There is compelling evidence to suggest the physical
heart is coupled to a eld of information not bound
by the classical limits of time and space.[243, 244] This
evidence comes from a rigorous experimental study
that demonstrated the heart receives and processes
information about a future event before the event
actually happens.[243, 244]
Figure 7.2. The heart’s pre-stimulus response. The graph
shows group averages of the heart rate variability (blue and
red lines) and skin conductance level (pink and green lines)
responses. The “0” time point denotes when the photos were
rst shown, when participants saw either an emotionally
arousing or calm picture. Pre-stimulus responses which
indicate nonlocal intuition are in the period between −6 and 0
seconds. The red line is the HRV trace when the future photo
was an emotional one, and the blue line shows the HRV for
calming future photos. The highly significant difference
between the HRV responses in the pre-stimulus period before
the future calm or emotional photos can clearly be seen
starting to diverge approximately 4.8 seconds prior to the
participants actually seeing the photos.
Chapter 7: Intuition Research: Coherence and the Surprising Role of the Heart
48
© Copyright 2015 HeartMath Institute
Science of the Heart
Extending and building on Radin’s protocol designed
to evoke an emotional response using randomly se-
lected, emotionally arousing or calming photographs,
we added measures of brain response (EEG) and
heart-rhythm activity (ECG) and found that not only
did both the brain and heart receive the pre-stimulus
information some 4 to 5 seconds before a future emo-
tional picture was randomly selected by the computer,
the heart actually received this information about 1.5
seconds before the brain received it (Figure 7.3).[244]
Figure 7.3. Example of temporal dynamics of heart and brain
pre-stimulus responses: This overlay plot shows the mean
event-related potential (ERP) at EEG site FP2 and heart-rate
deceleration curves during the pre-stimulus period. (The “0”
time point denotes stimulus onset.) The heart-rate deceleration
curve for the trials, in which a negative emotionally arousing
photo would be seen in the future, diverged from that of
trials containing a calming future picture (sharp downward
shift) about 4.8 seconds before the stimulus (arrow 1). The
emotional trials ERP showed a sharp positive shift about 3.5
seconds before the stimulus (arrow 2). This positive shift in
the ERP indicates when the brain “knew” the nature of the
future stimulus. The time difference between these two events
suggests that the heart received the intuitive information about
1.3 seconds before the brain. Heartbeat-evoked potential
analysis conrmed that a different afferent signal was sent
by the heart to the brain during this period.
[244]
A number of studies have since found evidence of the
heart’s role in reecting future or distant events.[245-251]
Using a combination of cortical-evoked potentials and
heartbeat-evoked potentials, these studies also found
that when the participants were in the physiological
coherence mode before the trials, the afferent input
from the heart and cardiovascular system modulated
changes in the brain’s electrical activity, especially
at the frontal areas of the brain. In other words, par-
ticipants were more attuned to information from the
heart while in a coherent state before participating
in the experimental protocol. Therefore, being in a
state of psychophysiological coherence is expected
to enhance intuitive ability.[244]
This suggests the heart is directly coupled to a source
of information that interacts with the multiplicity of
energetic elds in which the body is embedded. We
also found further evidence that the magnitude of pre-
stimulus response to a future event is related to the
degree of emotionality associated with that event.[243]
Nonlocal Intuition in Repeat
Entrepreneurs
A study conducted in Iran with a group of 30 repeat
entrepreneurs in the science and technology parks
of the city of Tehran duplicated and extended our
rst study of intuition.[251] Repeat entrepreneurs were
chosen for this study because they are most likely to
have demonstrated that their success is not the result
of luck alone and they have beaten the odds against
success. Also, studies have shown that they have a
strong tendency to rely on their intuitions when mak-
ing important business decisions. The study was mod-
eled after our study, described above, whose stimulus
was a computer-administered random sequence of
calm and emotional pictures. However, this study
added a new element: Researchers conducted two
separate experiments.
The rst, with a group of single participants (N = 15),
and the second, with a group of co-participant pairs
(N = 30), investigated the “amplication” of intuition
effects by social connection. In the experiment for
single participants, the participant watched the pic-
tures on a monitor alone, while in the experiment for
49
© Copyright 2015 HeartMath Institute
co-participant pairs, each pair watched the same
pictures simultaneously on two monitors while sitting
facing each other, as illustrated in Figure 7.4.
Each experiment was conducted over 45 trials while
heart-rate rhythm activity was recorded continuously.
In both experiments, the results showed signicant
pre-stimulus results, meaning for the period before the
computer had randomly selected the picture stimu-
lus. Moreover, while signicant separation between
the emotional and calm HRV curves was observed
in the single-participant experiment, an even larger
separation was apparent for the experiment with
co-participant pairs, and the difference between the
two groups also was signicant. Overall, the results
of the single-participant experiment conrm our and
others’ previous finding that electrophysiological
measures, especially changes in heart rhythm, can
demonstrate intuitive foreknowledge. This result is
notable because, having come from experiments in
Iran, it constituted cross-cultural corroboration in a
non-Western context. In addition, the results for co-
participant pairs offer new evidence on the amplica-
tion of the nonlocal intuition signal.
Full-Moon Effect on Amplifying Intuition
We also evaluated an updated version of a roulette
protocol we developed that includes two pre-stimulus
segments. This study included an analysis of indi-
vidual data analysis and group-level data analysis for
13 participants over eight separate trials.[252] We also
assessed the potential effects of the moon phase on
the pre-stimulus response outcomes and participant
winning and amount-won ratios. Half of the experi-
Chapter 7: Intuition Research: Coherence and the Surprising Role of the Heart
mental sessions were conducted during the full-moon
phase and half during the new-moon phase. Within
each trial, a total of three segments of physiological
data were assessed. There were two separate pre-
stimulus periods, a pre-bet (4-seconds) and post-bet
(12-seconds), and a post-result period (6-seconds).
Participants were told they were participating in a
gambling experiment, given an initial starting kitty
and informed that they could keep any winnings over
the course of 26 trials for each of the eight sessions.
The physiological measures included the ECG, from
which cardiac interbeat intervals (HRV) were derived
and skin conductance.
Overall, the results indicate the protocol provides an
effective objective method for measuring and detect-
ing a pre-stimulus response, which demonstrates a
type of nonlocal intuition. We found signicant dif-
ferences between the win and loss responses in the
aggregated physiological waveform data during both
pre-stimulus segments (Figure 7.5).
On average, we detected a signicant pre-stimulus
response starting around 18 seconds before partici-
pants knew the future outcome. Interestingly, there
was not a strong overall relationship between the
pre-stimulus responses and the amount of money the
participants won or lost. We also found a signicant
difference in both pre-stimulus periods during the full-
moon phase, when they also won more money, but not
in the new-moon phase (Figure 7.6). Overall, the nd-
ings also suggest that if participants had been able to
become more attuned to their internal cardiac related
pre-stimulus responses, they would have performed
much better on the betting choices they made.
Figure 7.4. Setup for Single Participant Experiment and Co-participant Pair Experiment.
50
© Copyright 2015 HeartMath Institute
Science of the Heart
Figure 7.5. Multisession roulette paradigm study: Grand averages are shown for the skin conductance levels and HRV win/loss
waveform differences in response to winning or losing for all 13 participants across all eight trials for the three segments of the
experiment: pre-bet, post-bet and post-result periods. * = (p < 0.05), ** = (p < 0.01), *** = (p < 0.001)
Figure 7.6. Multisession roulette paradigm study: Shown are grand averages by moon phase for the skin conductance levels
and HRV win/loss waveforms results. There was a signicant difference in the HRV win/loss waveforms in both the pre-bet
(p < 0.01) and post-bet (p < 0.05) periods during the full-moon phase and no signicant difference during the new-moon phase.
* = (p < 0.05), ** = (p < 0.01), *** = (p < 0.001)
51
© Copyright 2015 HeartMath Institute
Heart Intelligence
Because the heart plays a central role in creating
physiological coherence and is associated with heart-
felt positive emotions and intuition, it is not surprising
that one of the strongest threads uniting the views of
diverse cultures and religious and spiritual traditions
throughout history has been a universal regard that it
is the source of love, wisdom, intuition, courage, etc.
Everyone is familiar with such expressions as “put
your heart into it,” “learn it by heart” and “speak from
your heart.” All of these suggest an implicit knowledge
that the heart is more than a physical pump that
sustains life. Such expressions reect what often is
called the intuitive, or spiritual heart. Throughout his-
tory, people have turned to the intuitive heart – also
referred to as their inner voice, soul or higher power
– as a source of wisdom and guidance.
We suggest that the terms intuitive heart and spiritual
heart refer to our energetic heart, which we believe is
coupled with a deeper part of ourselves. Many refer to
this as their higher self or higher capacities, or what
physicist David Bohm described as “our implicate
order and undivided wholeness.[235] We use the term
energetic systems in this context to refer to the func-
tions we cannot directly measure, touch or see, such
as our emotions, thoughts and intuitions. Although
these functions have loose correlations with biologi-
cal activity patterns, they nevertheless remain covert
and hidden from direct observation. Several notable
scientists have proposed that such functions operate
primarily in the frequency domain outside of time and
space and they have suggested some of the possible
mechanisms that govern how they are able to interact
with biological processes.[206, 253-259]
As discussed in the Heart-Brain Communication
chapter of this work, the physical heart has extensive
afferent connections to the brain and can modulate
perception and emotional experience.[5] Our experi-
ence suggests that the physical heart also has com-
munication channels connecting it with the energetic
heart.[244] Nonlocal intuition, therefore, is transforma-
tional, and from our perspective, it contains the wis-
dom that streams from the soul’s higher information
eld down into the psychophysiological system via
the energetic heart and can inform our moment-to-
moment experiences and interactions. At HeartMath
Institute, this is what we call heart intelligence.
Heart intelligence is the ow of higher awareness
and the intuition we experience when the mind and
emotions are brought into synchronistic alignment
with the energetic heart. When we are heart-centered
and coherent, we have a tighter coupling and closer
alignment with our deeper source of intuitive intelli-
gence. We are able to more intelligently self-regulate
our thoughts and emotions and over time this lifts
consciousness and establishes a new internal physi-
ological and psychological baseline.[244] In other words,
there is an increased ow of intuitive information that
is communicated via the emotional energetic system
to the mind and brain systems, resulting in a stronger
connection with our deeper inner voice.
Accessing Intuition
Although people’s degree of access to the heart’s
intuition varies, we all have access to the three types
of intuition. As we learn to slow down our minds and
attune to our deeper heart feelings, a natural intuitive
connection can occur. Intuition often is thought of in
the context of inventing a new lightbulb or winning
in Las Vegas, but what most people discover is that
intuition is a very practical asset that can help guide
their moment-to-moment choices and decisions in
daily life. Our intuitive insights often unfold more
understanding of ourselves, others, issues and life
than years of accumulated knowledge. It is especially
helpful for eliminating unnecessary energy expendi-
tures, which deplete our internal reserves, making it
more dicult to self-regulate and be in charge of our
attitudes, emotions and behaviors in ordinary day-
to-day life situations. Intuition allows us to increase
our ability to move beyond automatic reactions and
perceptions. It helps us make more intelligent deci-
sions from a deeper source of wisdom, intelligence
and balanced discernment, in essence increasing
our consciousness, happiness and the quality of our
life experience. This increases synchronicities and
enhances our creativity and ability to ow through
Chapter 7: Intuition Research: Coherence and the Surprising Role of the Heart
52
© Copyright 2015 HeartMath Institute
Science of the Heart
life. It also increases our ability to handle awkward
situations such as dealing with dicult people with
more ease and it promotes harmonious interaction
and connectivity with others.
It is important to understand that conscious aware-
ness of anything, including our emotions and intui-
tive promptings, is not possible until something has
captured our attention.[260] Sensory neurons in our
eyes, ears, nose and body are continuously active day
and night, whether we are awake or asleep. The brain
receives a steady stream of information about all the
events the sensory systems are detecting. It would
be bewildering if we were continuously aware of all
the incoming information from both our external and
internal environments. In fact, we completely ignore
most of the information arriving to the brain – most of
the time. It is when inputs are large, sudden or novel
or lead to an emotional reaction that they capture
and focus our attention and that we become aware
of them.[206]
Voluntary attention, on the other hand, describes the
process in which we can consciously self-regulate
and determine the contents of our own awareness
as well as the duration of our focus. Current evidence
suggests that this self-regulatory capacity relies on an
inner resource akin to energy, which is used to inter-
rupt the stream of consciousness and behavior and
alter it. When this limited energy has been depleted,
further efforts at self-regulation are less successful
than usual.[261] With practice, however, the capacity to
self-regulate can be increased and give us more energy
resources to sustain self-directed control. Importantly,
these practices also are keys to establishing a new
baseline and once a new baseline is established, the
new patterns of self-regulation become automatic and
therefore do not require the same energy expenditure.
One of the most important keys to accessing more of
our intuitive intelligence and inner sense of knowing
is developing deeper levels of self-awareness of our
more subtle feelings and perceptions, which otherwise
never rise to conscious awareness. In other words,
we have to pay attention to the intuitive signals that
often are under the radar of conscious perception
or are drowned out by ongoing mental chatter and
emotional unrest. A common report from people who
practice being more self-aware of their inner signals
is that the heart communicates a steady stream of
intuitive information to the mind and brain. In many
cases, we only perceive a small percentage of intuitive
information or choose to override the signals because
they do not match our more egocentric desires.
Given that there is a relationship between increased
heart coherence and access to intuitive signals,[244]
the capacity to shift into a coherent state is an im-
portant factor in the three types of intuition: implicit
knowledge/learning, energetic sensitivity and nonlocal
intuition. The research discussed above suggests it’s
possible to access intuitive intelligence more effective-
ly by rst getting into a coherent state, quieting mental
chatter and emotional unrest and paying attention to
shifts in our feelings, a process that brings intuitive
signals to conscious awareness.[262] We have found
that increased heart-rhythm coherence correlates with
signicant improvements in performance on tasks
requiring attentional focus and subtle discrimination.
[5] We’ve also found that heart-rhythm coherence cor-
relates with pre-stimulus-related afferent (ascending)
signals from the heart to the brain.[244]
It is likely that these signals are important elements
of intuition that are particularly salient in pattern
recognition and that they are involved in all types of
intuitive processes.
The Freeze Frame Technique,[179, 182] is a ve-step pro cess
that was designed for improving intuitive capacities,
stopping energy drains, shifting perspective, obtain-
ing greater clarity and nding innovative solutions to
problems or issues.
53
© Copyright 2015 HeartMath Institute
Health Outcome Studies
“Natural forces within us are the true healers of disease.” —Hippocrates
An estimated 60% to 80% of primary-care doctor visits are related to stress.[60-62] HeartMath’s easily learned
mental and emotion self-regulation techniques and practices can provide an effective strategy for stress
reduction in many clinical contexts. As discussed earlier, these intentionally simple techniques allow people
to quickly self-induce a physiological shift to a more coherent state that takes advantage of the concurrent
change in afferent neuronal input to the brain, which is associated with increased self-regulatory capacity and
thus, ability to more successfully handle the demands and challenges of life with more ease and composure.
Consequently, there is a greater experience of connectedness, harmony, balance and physical, emotional and
psychosocial well-being.
Chapter 8: Health Outcome Studies
HeartMath interventions have facilitated
health improvements in patients with:
Hypertension
Arrhythmias
Autoimmune
disorders
Environmental
sensitivity
Sleep disorders
Drug and alcohol
addiction
Anger
Heart failure
Chronic pain
Fibromyalgia
Chronic
fatigue
Anxiety disorders
Depression
PTSD
ADD/ADHD
Eating disorders
Health-care professionals worldwide, representing
both mental health and medical elds, are incorpo-
rating HeartMath self-regulation techniques and
practices into their treatment strategies with notable
success. A growing number of clinical studies and
case histories have documented substantial reduc-
tions in symptomatology and improvements in clinical
status in a wide variety of conditions after a relatively
brief time when their patients use these techniques
and practices. Collectively, results indicate that such
self-regulation techniques are easily learned and
employed, produce rapid improvements, have a high
rate of compliance, can be sustained over time and
are readily adaptable to a wide range of age and de-
mographic groups.
The use of interventions utilizing the HeartMath self-
regulation techniques and HRV coherence feedback
technology to reduce stress has signicantly improved
key markers of health and wellness. For example,
studies have shown the use of these self-regulation
techniques increases parasympathetic activity (HF
power) [133] and results in signicant reductions in
cortisol and increases in DHEA (Figure 8.1) over a
30-day period [116]. In a study for which results are
shown in the gure, 30 participants were taught the
Cut-Thru and Heart Lock-In self-regulation techniques
and practiced using them in daily life for one month.
The signicant changes in hormonal balance corre-
lated with the signicant improvements in emotional
health and reductions in stress, anxiety, burnout and
guilt along with increases in caring and vigor.
Figure 8.1. DHEA and cortisol values before and after subjects
were trained in and practiced HeartMath self-regulation
techniques for one month. There was a 100% average increase
in DHEA and a 23% decrease in cortisol.
CHAPTER 8
54
© Copyright 2015 HeartMath Institute
Science of the Heart
Coherence and Blood Pressure
Several studies have shown signicantly lowered
blood pressure (BP) and stress measures. Employees
with a diagnosis of hypertension who were enrolled in
a workplace-based risk-reduction program exhibited
signicant reductions in blood pressure relative to the
control group after using HeartMath tools for three
months.[115] Participants also experienced signicant
reductions in distress and depression, concurrent with
improvements in work performance-related param-
eters following the intervention (Figure 8.2).
Figure 8.2. Changes in systolic and diastolic blood pressure
in the HeartMath group versus the control group. BP was
measured before and three months after the completion of
the training program. The trained group demonstrated a mean
adjusted reduction of 10.6 mm Hg in systolic BP and of 6.3 mm
Hg in diastolic BP. (Three-month measurements are adjusted
for baseline BP, age, gender, body mass index and medication
status.) *p < .05.
The trained group demonstrated a mean adjusted
reduction of 10.6 mm Hg in systolic BP and of 6.3
mm Hg in diastolic BP, as compared to reductions
of 3.7 mm Hg (systolic) and 3.9 mm Hg (diastolic) in
the control group. In addition, three individuals in the
trained group were able to reduce their BP medica-
tion usage, with their physicians’ approval, during the
study period. Of these, one participant was permitted
to discontinue antihypertensive medication usage
entirely following completion of the study. These BP
improvements achieved by the treatment group are
notable when viewed in comparison to BP reductions
typically achieved with other types of interventions.
The reduction in BP obtained through the stress-
management training is similar in magnitude to the
average reduction in BP reported in a meta-analysis
of controlled trials of anti-hypertensive drug therapy
that lasted for several years. This reduction in BP is the
equivalent of a 40-pound weight loss, and is twice the
size of the average reduction seen with, for example,
a low-salt diet or exercise training.[263-265]
In another study of hypertensive patients, it was found
that those who used the techniques to increase HRV
coherence had rapid reductions, on average, of 10mm
Hg in mean BP. The study was a randomized controlled
design with 62 hypertensive participants who were
divided into three groups. (Group 1 participants were
taking hypertensive medications and taught the Quick
Coherence self-regulation technique and used a heart
rate variability (HRV) coherence-training device. Group
2 members were not yet taking medications and were
trained in the Quick Coherence Technique; those in
Group 3 were taking hypertensive medications and
did not use the Quick Coherence Technique, but in-
stead were instructed in a relaxation technique that
they used between the BP assessments. An ANCOVA
(analysis of covariance) was conducted to compare
the effectiveness of three different interventions at
reducing blood pressure. The two groups that used
the Quick Coherence self-regulation technique and
HRV coherence-training device were associated with
a signicantly greater reduction in systolic and mean
arterial pressure (average blood pressure) compared
with the medication/relaxation technique-only group.
The greatest reductions in blood pressure were associ-
ated with the combination of medications and the use
of the HRV coherence device and the self-regulation
technique. Surprisingly, the group that was not taking
medications had greater reductions than the medica-
tions/relaxation group (Figure 8.3).[113]
Health Risk Reduction in Correctional
Ocers
A study of 88 California correctional ocers with high
workplace stress was randomized to experimental
and wait-list control groups, stratified on relative
health risk, age and gender.[266] The experimental group
participated in a stress- and health-risk reduction pro-
gram, which was delivered over two consecutive days.
55
© Copyright 2015 HeartMath Institute
Figure 8.3. Shows the pre-post intervention changes in systolic, diastolic and mean arterial blood pressure for the three groups.
The use of the Quick Coherence self-regulation technique and HRV coherence-training device was associated with a signicantly
greater reduction in systolic and mean arterial pressure (average blood pressure) in the two groups who used the intervention
compared with the medication/relaxation technique-only group. The greatest reductions in blood pressure were associated with
the combination of medications and the intervention using the HRV device and self-regulation technique.
The program included instruction on health-risk factors as well as training in HeartMath’s self-regulation tech-
niques. Learning and practice of the techniques were enhanced by HRV coherence feedback. Physiological
changes in the experimental group included signicant reductions in total cholesterol, LDL cholesterol levels,
the total cholesterol/HDL ratio, fasting glucose levels, mean heart rate, mean arterial pressure, and both systolic
and diastolic blood pressure (Figure 8.4).
N = 43
Total Cholesterol
***
180
190
200
210
220
230
Pre Post
mg/dL
HDL Cholesterol
40
42
44
46
48
Pre Post
mg/dL
LDL Cholesterol
***
110
120
130
140
150
160
Pre Post
mg/dL
Glucose
**
90
95
100
105
110
Pre Post
mg/dL
Systolic Blood
Pressure
***
112
114
116
118
120
122
124
126
Pre Post
mm Hg
Diastolic Blood
Pressure
**
74
76
78
80
82
84
Pre Post
mm Hg
Heart Rate
*
64
66
68
70
72
74
76
78
Pre Post
BPM
Figure 8.4. Bar graphs illustrate physiological variables in the experimental group, measured before and three months after the
intervention program. The group showed signicant reductions in total cholesterol, LDL cholesterol, blood glucose levels, systolic
and diastolic blood pressure, and heart rate after the intervention. *p < 0.05, **p < 0.01, ***p < 0.001.
Chapter 8: Health Outcome Studies
56
© Copyright 2015 HeartMath Institute
Science of the Heart
Psychological changes included signicant reduc-
tions in overall psychological distress, anger, fatigue,
hostility, interpersonal sensitivity, impatience, and
global Type A behavior, and increases in gratitude and
positive outlook. There were also improvements in
key organizationally relevant measures in the experi-
mental group after the program, including signicant
increases in productivity, motivation, goal clarity and
perceived manager support. Finally, a detailed analysis
was performed to calculate the projected health-care
cost savings to the organization that would likely
result from the reduction in participants’ health risk
factors. According to this analysis, the reductions in
health-risk factors achieved in this study were pro-
jected to lead to an average health-care cost savings
of $1,179 per employee per year.
Health-Care Cost Reduction
The Reformed Church in America (RCA) identied
stress among its clergy as a major cause of higher-
than-average health claims. Because the pastors were
spread across the U.S., the intervention was provided
by a small team of HeartMath certied mentors in
six phone sessions to help the participants manage
stress and increase physiological resilience. The
study divided 313 participants into two groups with
149 participating in the HeartMath program deliv-
ered by phone, which included instruction in use of
the portable version of the emWave and practice of
the self-regulation techniques and 164 in the active
control group participated in a phone-based lifestyle-
management program. All participants completed a
health-risk assessment and a validated HeartMath
Stress and Well-being Survey at the beginning of
2007 and again at the beginning of 2008. Well-being,
stress management, resilience, and emotional vitality
were signicantly improved in the HeartMath group
compared to the lifestyle-management group. In an
analysis of the claims costs data for that year, the
pastors who had participated in the HeartMath pro-
gram were compared to the control group. Adjusted
medical costs were reduced by 3.8% for HeartMath
participants while there was an increase of 9.0% for
the control group. The adjusted pharmacy costs in-
creased 7.9% for the HeartMath group and 13.3% for
the control group. The total 2008 savings as a result
of the program were $585 per participant, yielding a
return on investment of 1.95:1. In the detailed medical
cost analysis, one of the higher cost-savings catego-
ries was for essential hypertension, which would be
expected to be sensitive to reduced stress.[112]
Metabolic Syndrome
A number of signicant health outcomes were found in
two workplace pilot studies of utility line workers and
employees of an online travel company. These studies
focused on reducing stress and metabolic syndrome
risk factors with the HM self-regulation techniques
combined with HRV coherence feedback. In both stud-
ies, there were signicant reductions in organizational
stress (life pressures, relational tensions, work-related
stress), emotional stress (anxiety, depression, anger)
and stress symptoms (fatigue, sleep, headaches,
etc.), and signicant increases in emotional vitality.
Both studies also showed reductions in the number
of participants who were classied as having meta-
bolic syndrome. In the utility-company cohort, total
cholesterol and LDL cholesterol were signicantly
reduced, and the travel-company cohort had signi-
cant reductions in both systolic and diastolic BP and
triglycerides (unpublished data).
Asthma/Pulmonary Function
One of the reasons coherence training is an effec-
tive approach for reducing both short-term and
long-term BP, may be a resting of baroreex gain.
Psychophysiologist Paul Lehrer, has shown that us-
ing HRV feedback to promote a state of physiological
coherence, which he calls “resonance,” resulted in
lasting increases in baroreex gain, independent of
respiratory and cardiovascular changes.[111] In a large
controlled study involving patients with asthma, those
using the HRV resonance training had improved lung
function, decreased symptoms, exhibited no asthma
exacerbations and were able to reduce steroid medica-
tions.[267] In other studies, Lehrer demonstrated that
pulmonary function improvements occurred in both
older and younger patients even though older individu-
als have lower HRV[183] and that the improvements
57
© Copyright 2015 HeartMath Institute
group or wait-listed control group. The intervention was
provided in eight weekly sessions over a 10-week period.
Signicant improvements were noted in perceived stress,
emotional distress, six-minute walk and depression, and
positive trends were noted in each of the other psychoso-
cial measures. The investigators noted that CHF patients
were very willing participants and the study suggested
that HeartMath techniques were a feasible and ef-
fective intervention for CHF patients, demonstrating
that stress and depression levels could be reduced
and functional capacity increased in this popula-
tion through training in emotion self-management.
This study’s promising indications clearly warrant
larger-scale controlled trials to conrm the observed
psychosocial and functional improvements and fur-
ther explore the implications of such outcomes for
physiological rehabilitation (Figure 8.5-8.7).
occur with HRV biofeedback training, but not with
relaxed breathing or muscle tension relaxation.[268]
He also published a report of 20 case studies which
showed uniform improvements in pulmonary function
in children with asthma.[269] Additionally, according to
Lehrer, in a controlled study, patients with multiple
unexplained symptoms and depression[270] showed
improvements, as did patients with bromyalgia[271]
and major depression.[272]
Congestive Heart Failure
A study was conducted at Stanford University to evalu-
ate the effect of the HeartMath self-regulation skills
training on quality of life and functional capacity in
elderly patients with class I–III congestive heart failure
(CHF).[192] Thirty-three multiethnic patients (mean age,
66±9 years) were randomly assigned to a treatment
Figure 8.5. Reduction in stress in
congestive-heart-failure patients
after the HeartMath training program.
Stress dropped 22% in the treatment
group following the intervention,
while it rose 7% in the control group
over the three-month study period.
(Perceived Stress Scale) ***p < .001.
Figure 8.6. Reduction in depression
in congestive-heart-failure patients
after the HeartMath training program.
Depression decreased by 34% in the
treatment group whereas it increased
by 13% in the control group over the
study period. (Geriatric Depression
Scale) *p < .05.
Figure 8.7. Improvements in functional capacity
in congestive-heart-failure patients after the
HeartMath program. Functional capacity, as
measured by performance on the six-minute
walk, increased 14% in the treatment group
while it declined 2% in the control group.
Treatment-group participants were able to walk
an average of 153 feet further in six minutes at
posttest than at pretest. *p < .05.
Diabetes
In a study of diabetes patients, the introduction of the self-regulation skills led to an improved overall quality
of life and glycemic regulation, which correlated with use of the self-regulation techniques.[273] Twenty-two pa-
tients with Type 1 or Type 2 diabetes mellitus participated in a two-day training. Hemoglobin A1c, cholesterol
and triglycerides, and blood pressure were assessed along with measures of stress, psychological status and
quality of life before and six months following the training. There were signicant reductions in psychological
symptomatology and negative emotions, including anxiety, depression, anger and distress and signicant in-
Chapter 8: Health Outcome Studies
58
© Copyright 2015 HeartMath Institute
Science of the Heart
creases in peacefulness, social support and vitality,
as well as reductions in somatization, sleeplessness
and fatigue.
Figure 8.8. Diabetic patients demonstrated significant
reductions in a numerous psychological symptoms (Brief
Symptom Inventory) after practicing the HeartMath
interventions for six months. *p < .05.
Figure 8.9. The graph on the left illustrates the signicant
increase in the group’s mean overall quality of life raw score, as
measured by the Quality of Life Inventory three weeks before
versus six months after the HeartMath program. The graph
on the right plots the mean overall quality of life percentile
score for study participants as compared to normative data.
Before the intervention program, the group’s mean percentile
score plotted very near the bottom of the average range,
whereas six months after the program it had moved into the
high range. **p < .01.
Participants also showed reduced sensitivity to daily
life stressors, and quality of life signicantly improved
(Figures 8.8 and 9). Regression analysis revealed a
signicant relationship between self-reported prac-
tice of the techniques learned in the program and
the change in HbA1c levels in patients with Type 2
diabetes with more practice being associated with
reductions in HbA1c.
Coherence and Improved Cognitive
Function
Several studies have shown that increased levels
of heart-rhythm coherence are associated with sig-
nicant improvements in cognitive performance.[5,
108, 109] Signicant outcomes have been observed in
discrimination-and reaction-time experiments and
more complex domains of cognitive function, includ-
ing memory and academic performance.[5, 274] In terms
of healthier cognitive and emotional functioning,
signicant reductions in stress, depression, anxiety,
anger, hostility, burnout and fatigue, and increases in
caring, contentment, gratitude, peacefulness, resil-
ience and vitality have been measured across diverse
populations.[275-280]
Attention Decit Hyperactivity Disorder
(ADHD)
ADHD, the most commonly studied and diagnosed
behavioral condition in childhood, is estimated to
affect 3% to 5% of children globally. Left untreated,
ADHD can lead to academic underachievement, poor
interpersonal relationships, anxiety, depression and
increased risk of criminal activity. Of particular con-
cern is the increased risk of mental health problems
for adolescents with ADHD.
A randomized blind, placebo-controlled study was
undertaken with 38 children (aged 9 to 13) with a clini-
cal diagnosis of ADHD in Liverpool, England to assess
the potential benets of HeartMath self-regulation
techniques. Learning the skills was supported by HRV
coherence feedback training. The placebo control con-
sisted of daily 20-minute, one-on-one sessions with
a learning assistant for six weeks. During these ses-
sions, each child was free to build a model of choice
from Lego building blocks. Cognitive function was as-
sessed using a comprehensive set of computer-based
tests of attention, concentration, vigilance, short-term
(working) memory and long-term (episodic) memory
59
© Copyright 2015 HeartMath Institute
before the intervention and again six weeks later.
Secondary measures included the Conners’ Teach-
ers Rating Scale and the Strengths and Diculties
Questionnaire completed by both children and their
teachers. After the post-intervention measures were
collected, the control group was provided with the
same HeartMath self-regulation skills program. Par-
ticipants demonstrated signicant improvements in
various aspects of episodic secondary verbal memory,
including delayed word recall and immediate word
recall and word recognition (Figure 8.10). Signicant
improvements in behavior also were found. The results
suggest that the intervention offers a physiologically
based program to improve cognitive functioning and
behaviors in children with ADHD.[108]
Delayed Word Recall
Quality of Verbal Episodic Secondary Memory
HM Only Group (N=14)
*
0
10
20
30
40
50
Before HM After HM
Words correctly recalled (%)
Active Wating Control (N=21)
**
0
10
20
30
40
50
Before Lego After Lego After HM
Words correctly recalled (%)
Active Wating Control (N=21)
**
0
50
100
150
200
Before Lego After Lego After HM
Index %
HM Only Group (N=14)
***
0
50
100
150
200
Before HM After HM
Index %
Figure 8.10. Children with ADHD in the HeartMath group
exhibited signicant increases in overall quality of episodic
memory and long-term memory. Children in the placebo-
control group (Lego play) showed a small, but non signicant
improvement over the same time period. There was a
signicant improvement in the control group as well after they
learned and practiced the HeartMath skills. Quality of verbal
episodic memory is a composite measure constructed from
accuracy measures of four cognitive function tests. *p < 0.05,
** p < 0.01, *** p < 0.01.
Improved Mental Health in Children
A study conducted by the Department of Psycho-
physiology at an outpatient pediatric clinic in Skopje,
Macedonia evaluated the effectiveness of HRV co-
herence training and the HeartMath self-regulation
techniques in the treatment of common mental health
disorders in children.[281] Six groups of children were
evaluated: a) children with anxious phobic symp-
toms, N = 15, mean age 12.5 ± 2.25 years; b) children
with somatoform problems (somatic symptoms not
explained by a general medical condition), N = 15,
mean age 10.92 ± 2.06; c) children with obsessive-
compulsive manifestations (OCD), N = 7; mean age
14.5 ± 2.20; d) children with ADHD, N = 10, mean age
10.5 ±.1.80; e) children with conduct disorders (CD),
N = 12, mean age 11.5 ± 1.52; and f) a control group,
N = 15 children, mean age 10.18 ± 1.33. All of the
examined children (N = 74) were of similar age. The
diagnosis was made according to ICD-10 classica-
tion by a team of pediatrician-psychophysiologists, a
clinical psychologist and a child neurologist. All chil-
dren were outpatients at the Skopje pediatric clinic.
In the assessment procedure, interviews with parents
and children and psychometric evaluations with the
Eysenck Personality Questionnaire (EPQ) were used
to discriminate four main psychological personality
characteristics: extroversion/introversion; neurotic
tendencies/stability; psychopathologic traits/normal
behavior; and self-control/lie scale.
The biofeedback instrumentation used was Heart-
Math’s HRV coherence-training system (Freeze-
Framer, now called emWave Pro). It was used to
reinforce the self-regulation techniques. Each patient
sat in a comfortable chair in a quiet room with the
practitioner. Patients were instructed to practice
a self-regulation technique that included rhythmic
heart-focused breathing and to activate a positive
emotion. After the initial assessment, 15 training ses-
sions were provided. The duration of all sessions was
about 16 minutes and included playing two games
(Meadow and Balloon), which are controlled by the
subject’s heart-coherence level.
Chapter 8: Health Outcome Studies
60
© Copyright 2015 HeartMath Institute
Science of the Heart
The results were statistically elaborated with: ANOVA
(analysis of variance) for the rst and last sessions of
all groups and Student t-test for differences between
groups. Generally, all children manifesting mental
health problems showed lower scores for extroversion
and higher scores for neuroticism, compared to the
control group at baseline. This nding was considered
important in the choice of biofeedback modality.
Namely, for introvert personalities, manifesting so-
called “inner arousal,” the application of peripheral
biofeedback modalities was considered to be a better
choice. In this context, peripheral biofeedback based
on HRV coherence was chosen for the study.
It was found in the results analysis that signicantly
lower heart rate between the rst and last session
were obtained for obsessive-compulsive and conduct
disorders and anxiety. It means that with training, al-
most all children, except the ADHD group, learned to
lower their heart rate. The Anxiety group showed very
good results related to HRV; they were able to increase
HRV coherence scores. For children with somatoform
problems, there also were signicant increases in
HRV parameters (VLF, LF and HF power). Changes in
HRV in the OCD group also had signicant increases
in all HRV measures, which were considered to be an
important clinical outcome. The children with ADHD
did not have increased HRV. The coherence scores
increased in all training sessions for all groups, but
the highest increases were in the conduct disorder
group followed by the general anxiety group (32.5 and
30 respectively). It also improved signicantly in the
OCD and somatoform disorders groups. HRV train-
ing showed very positive results relative to clinical
outcomes, especially for children with conduct and
anxious-phobic disorders, and for obsessive-compul-
sive and somatoform disorders.
In general, the authors concluded that HRV coher-
ence training, as a peripheral biofeedback modality,
could be a good noninvasive choice, especially for
introverted children manifesting common mental
health problems, and that the approach has a good
cost-benet ratio. The games included in the training
are very engaging for children.
Coherence Training Improves Memory
In a study conducted by Keith Wesnes in London, 18
healthy adult participants (six females, 12 males, ages
20 to 53, mean 32 years) were recruited for a study to
assess the potential long-term effects of HeartMath
self-regulation skills and HRV coherence training on
cognitive performance.[282]
Cognitive function was assessed using a compre-
hensive set of computer-based tests for attention,
concentration, vigilance, short-term (working) memory
and long-term (episodic) memory before the interven-
tion and again seven weeks later. Each participant’s
ECG was recorded for a 10-minute period for HRV and
coherence analysis before administration of the cog-
nitive function test battery. In addition, participants
completed a short self-administered questionnaire
that measured calmness and alertness. After baseline
collection, the participants attended a training pro-
gram in which they learned the Freeze Frame, Heart
Lock-In, and Coherent Communication techniques,
and instruction in using the HRV coherence feedback
system (Freeze-Framer, now called emWave Pro).
They were asked to use the Freeze Frame Technique
whenever they experienced stress or emotional dis-
cord, and the Heart Lock-In Technique three times per
week for at least 10 minutes. In addition, they were
encouraged to practice the Coherent Communication
Technique when engaging in conversation with oth-
ers. Seven weeks later the participants completed the
same measures using exactly the same protocols as
were used and followed for baseline data collection.
The results of the pre- and post-analysis of the cogni-
tive performance tests showed signicant improve-
ment (p = 0.0049) in the quality of episodic (long-term)
memory and marginally signicant improvement (p =
0.078) in the quality of working (short-term) memory
(Figure 8.11). There was a positive trend in the com-
posite scores reecting the ability to pay attention
and the speed with which they were able to retrieve
information from memory. However, the improve-
ments in these measures did not quite reach statisti-
cal signicance. Analysis of the questionnaire data
showed that the research participants reported feeling
61
© Copyright 2015 HeartMath Institute
signicantly calmer at the end of the study than they
did at the beginning (t-test 2.44, p < 0.05). This nding
is notable, in that Dr. Wesnes reported the magnitude
of the improvement was signicantly higher than
the improvement in quality of memory obtained in a
large clinical 14-week trial of the effects of a phyto-
pharmaceutical memory enhancer (a gingko/ginseng
combination) on the memory of healthy volunteers.
Quality of Episodic Memory
p=.0049
210
220
230
240
250
260
270
280
Before After
Units
Erro r bars = SE M
Quality of Working Memory
p=.078
1.65
1.70
1.75
1.80
1.85
Before After
Units
Figure 8.11. Mean improvements in quality of episodic (long-
term) memory and quality of working (short-term) memory
after participants practiced HeartMath coherence-building
tools for seven weeks.
For HRV analysis, standard time and frequency
domain HRV measures and coherence levels were
computed. In relation to baseline measurement, a
signicant increase in heart-rhythm coherence (p <
0.001) was observed post-intervention before the
participants were administered the cognitive function
assessments. The group’s mean HRV power spectra
showing the pre-post differences are shown in Figure
8.12. The increase in power around the 0.1-hertz
frequency range indicates a pronounced increase in
heart-rhythm coherence, and it occurred even though
the participants were not specically instructed to
use any of the tools they had learned in the program.
In an effort to explain the observed pre-post changes
in the quality of episodic memory and in self-rated
calmness, two additional stepwise multiple regres-
sions were run. Of the 10 independent variables includ-
ed in each analysis, improvement in coherence was
the only variable with sucient statistical power to
meet the criterion for entry into the stepwise analysis.
The results show that the change in coherence is quite
strongly related to the observed changes in episodic
memory and calmness: it accounted for 21% of the
variance in the improvement in long-term memory
and 42% of the variance in the reported increase in
calmness.[5]
Group Mean HRV PSD
Pre
0
20
40
60
80
100
120
140
00.1 0.2 0.3 0.4
Hz
PSD (ms^2/Hz)
Post
0
20
40
60
80
100
120
140
00.1 0.2 0.3 0.4
Hz
PSD (ms^2/Hz)
Post
Pre
Figure 8.12. Group mean HRV power spectra calculated from
10-minute ECGs recorded before subjects completed the
cognitive performance assessments. The left-hand graph
shows the mean HRV power spectrum before participants
were trained in the HeartMath self-regulation techniques, while
the right-hand graph shows the mean power spectrum after
they learned and practiced the techniques for seven weeks.
Note the increase in power around the 0.1-hertz frequency
range, indicating a pronounced increase in heart-rhythm
coherence. This shift is particularly notable, as subjects were
not specically instructed to use the techniques during the
post-recording.
Self-Regulation, PTSD Chronic Pain and
Brain Injury
While overall health and wellness benets have been
associated with increased coherence, there is also
evidence related more specifically to high-stress
populations. A study at the William Jennings Bryan
Dorn Veterans Affairs Medical Center in Columbia,
S.C. of recently returning soldiers from Iraq who
were diagnosed with PTSD, found that relatively brief
periods of cardiac coherence training combined with
practicing the Quick Coherence Technique resulted in
signicant improvements in the ability to self-regulate
and signicant improvements in a wide range of cogni-
tive functions, which correlated with increased cardiac
coherence. The study also found that resting HRV data
in those with a PTSD diagnosis had lower levels of
HRV and lower levels of coherence than control sub-
jects without PTSD. Figure 8.13 shows the changes
in cognitive function measures, and Figure 8.14 is an
example of the typical changes in the HRV waveforms
and power spectra from one of the participants.[109]
Chapter 8: Health Outcome Studies
62
© Copyright 2015 HeartMath Institute
Science of the Heart
34
Figure 8.13. Improvements in various measures of cognitive function in recently returned combat veterans with PTSD, after learning
the Quick Coherence self-regulation technique and receiving heart-rhythm coherence feedback training using the emWave Pro.
Cognitive improvements co-occurred with increases in heart-rhythm coherence and overall HRV. * p < 0.05; ** p < 0.01.
Figure 8.14 (a and b) depicts the pre-and post-HRVB Training the R-R interval tachogram and power spectra density of one subject with PTSD.
Figure 8.14. Typical example of one of the participant’s HRV and power spectra: (a) HRV wave recording pre-training. (b) Power
spectrum of HRV. (c) HRV recording post-coherence feedback training. (d) Power spectrum.
63
© Copyright 2015 HeartMath Institute
In a study of patients with severe brain injury, it
was found that the emotion self-regulation training
combined with HRV coherence feedback resulted
in signicantly higher coherence ratios and higher
attention scores. Additionally, the families’ ratings
of participants’ emotional control correlated with
improved HRV indices.[283]
In a study of returning veterans with chronic pain,
pre- and post-measurements of HRV, HRV variables,
cardiac coherence, perceived pain, stress, negative
emotions and physical activity limitation were made
for both treatment and control groups. The treatment
group received instruction in the Quick Coherence self-
regulation technique, which incorporates controlled
breathing and the self-induction of a positive or neutral
emotion, along with the HRV coherence feedback de-
vice. The technique was practiced during four weekly
biofeedback training sessions and was followed by
a post-training assessment of pain, stress, and HRV.
Control participants simply returned to the lab for a
follow-up evaluation four weeks after the initial as-
sessment. The treatment group showed marked and
statistically signicant increases in coherence (191%)
along with signicant reductions in pain ratings (36%),
stress perception (16%), negative emotions (49%) and
physical activity limitations (42%).[284]
Another study conducted in an outpatient pain reha-
bilitation clinic in a university hospital rehabilitation
center in the Netherlands examined the benets of
adding the HeartMath self-regulation and HRV co-
herence training to a back school (BS) program for
patients with chronic, nonspecic low back pain to
explore the possible moderators of treatment suc-
cess.[285] The secondary objective was to test the
relationships between HRV coherence at discharge
with pain, disability and health perception. It was
hypothesized that higher change in coherence scores
would be related to changes in pain, disability and
health perception.
A total of 170 patients with chronic, nonspecic low
back pain were enrolled in the study. Of these, 89
patients were assigned to the standard back school
(BS) program and 81 were assigned for BS and heart-
coherence training (BS+HCT). Inclusion criteria were:
nonspecic lower back pain lasting at least three
months and age 18 or older. Exclusion criteria were:
mental (e.g. major psychiatric disorders) or physical
causes (e.g. cardiac or pulmonary disorders or use of
heart medication) or being currently treated for such.
A rehabilitation physician approved each participant’s
inclusion.
At baseline assessment before treatment (T0) and at
discharge (T1), the patients lled out a comprehensive
set of questionnaires, including demographics, the
Pain Disability Index (PDI), the Roland Morris Disability
Questionnaire (RMDQ), Numeric Rating Scale (NRS
pain) and the RAND 36. HCT was evaluated using a
standardized test procedure before HCT and at dis-
charge using a ve-minute HRV assessment.
The back school program was provided by experi-
enced physiotherapists on an individual basis. It
focused on the physical aspects, such as increase
in physical capacity or ergonomics, and behavioral
aspects, which could be cognitive behavioral- or
acceptance-based approaches. The duration was 12
weeks, two times per week in a cardio tness setting,
for a total of 24 hours in the BS group.
Training in heart coherence and the self-regulation
techniques was provided six times, once per week
in an individual setting with one hour per meeting,
for a total of six hours. Patients were trained in a
therapy setting and practiced using the techniques at
home. BS-HCT followed a standardized certication
program protocol by the HeartMath Institute (Heart-
Math Interventions Program). The rst HCT sessions
were focused on learning the basic self-regulation
techniques. After the patients learned the basic tech-
niques, they were exposed to stressors by focusing
on individualized negative feelings and emotions,
including their pain.
Both groups improved signicantly on NRS pain,
RMDQ, PDI and most of the Rand 36 subscales. On
physical functioning, the BS+HCT group improved
signicantly more than the BS only group (p=0.02).
Signicant correlations (r=0.39 and r=0.48) were
found between increased heart-coherence scores
and reduced PDI pain and RMDQ disability scores,
Chapter 8: Health Outcome Studies
64
© Copyright 2015 HeartMath Institute
Science of the Heart
but not with other variables. Providing BS-HCT was
more effective on physical functioning than the BS-
only program was.
Self-Regulation for Caregiver Settings
In recent years, an increasing number of studies on
stress have focused on professional caregivers. Af-
fected professionals speak of burnout to dene a
state of emotional and physical exhaustion caused by
the stressful demands of their daily work. The study
of these two conditions has been developed in areas
of high demand for services such as care for people
with dementia. Because dementia is a progressive,
disabling and long-term neurodegenerative disease,
the risks of being exposed to chronic stress situations
for both professional and family-member caregivers is
very high.[286] Many studies show the consequences of
professional stress, both emotional and physical, that
can cause communication problems in the team and
families and affect the general welfare of the person.
[287] Improving the ability of caregivers to effectively
meet the challenges of their daily work is valuable
not only for institutions because they will have work-
ers who are less stressed and healthier, but also for
people receiving care.[288]
A study conducted in three long-stay nursing homes
for elderly people located in different cities in Spain
examined the outcomes of providing stress-man-
agement intervention based on HeartMath’s self-
regulation techniques and heart-coherence training
with the emWave PSR (now called emWave2) in a
group of nursing professionals and family caregivers
of elderly patients with dementia.[289] The conceptual
nursing model that guided the implementation of this
study was Jean Watson’s theory of Human Care.[290]
Watson’s theory emphasizes the importance of tak-
ing care of oneself, colleagues or family and others
as a means of achieving a more healing environment.
Participants included 42 professionals (67.9% certied
nursing assistants) and 32 family-member caregiv-
ers. The only exclusion criterion was subjects with
sensory or cognitive impairment that prevented them
from understanding the training content. A number of
socio-demographic variables were collected, including
age, sex, occupation, education level, medical history,
drug use, years of caregiving and information about
people under their care, such as degree of dementia.
The degree of stress and burnout for the professional
caregivers was assessed with the Maslach Burnout
Inventory (MBI), which has three primary subscales:
emotional exhaustion, depersonalization and personal
accomplishment at work. For family caregivers, the
scale used to assess overload was the validated
Spanish version of the Zarit Burden Inventory, which
reects the level of overload a person is experiencing.
For measurement of heart coherence, the emWave Pro
was used to assess participants’ coherence levels at
pre- and three-months-post-training during resting
state and during a period in which they were asked to
relax. In addition, at the end of the workshops, partici-
pants’ lled out questionnaires on stress and overload,
and heart-coherence measures were obtained.
The self-regulation skills training was conducted in
workshop style with groups of 10 people, without dif-
ferentiating between professional and family caregiv-
ers. The workshops were provided in one-hour weekly
sessions, over a three-month period. Only people who
attended more than 80% of the workshops were in-
cluded in the analysis. The results of an ANOVA analy-
sis of the professional caregivers three months after
the training found a signicant reduction in the MBI
scales for emotional exhaustion and improvement in
performance. The depersonalization scale was not
signicantly changed. In the family caregivers group,
the Zarit scale results were not statistically conrmed
after a Bonferroni correction (p = .04). A noteworthy
nding among family caregivers was a high percent-
age of hypertension (43.7%), insomnia (28.7%) and
anxiety (31.8%), each of which required taking of at
least one drug on a daily basis. In professionals, the
most prevalent issues were sleep problems (27.8%)
and muscular or mechanical (47.6%) problems. Re-
garding heart-coherence scores, at baseline 58.7%
of all participants (n = 71) had low heart-coherence
scores. At post assessment, 86.4% of participants had
high heart coherence, with signicant increases over
the baseline values.
65
© Copyright 2015 HeartMath Institute
The authors concluded that the main objective of
this work was to reduce the levels of stress and
overload through increased psychological control
and increased heart coherence in a group of profes-
sionals and caregivers of people with dementia. The
results suggest that the intervention achieved the
main objective.
Physician Stress Reduction
Given the nature of their occupational duties and en-
vironment, physicians often experience work-related
stress that may lead to burnout, depression and
substance abuse, as well as impaired professional
performance. These may be indicated by medical er-
rors, reduced attentiveness or caring behavior toward
their patients and other staff members. Physician
wellness has been increasingly linked to the quality
of patient care, yet the attention that physicians pay
to self-wellness often is suboptimal.
A randomized controlled study conducted by Jane
Lemarie and colleagues at the University of Calgary
with 40 physicians (23 male and 17 female) from vari-
ous medical practices (1 from primary care, 30 from a
medical specialty and 9 from a surgical specialty) was
conducted to assess the ecacy of HeartMath self-
regulation skills training supported by HRV coherence
training (emWave2) for reducing physician stress.[291]
Participants in the intervention group were given an
HRV coherence training device and were instructed in
how to use it. They also participated in an individual
training session to learn the Quick Coherence self-
regulation technique and were instructed to use the
HRV device during the study for ve minutes at least
three times daily. A research assistant contacted each
participant in the intervention group twice weekly
to measure stress, heart rate, blood pressure and
overall well-being to document adherence to using
the stress-management techniques and to record
a three-minute HRV session using the emWave Pro
system. Participants in the control group received a
brochure describing the provincial physician wellness
support program and were contacted twice weekly by
a research assistant to measure stress, heart rate,
blood pressure and overall well-being.
The primary outcome, stress, was assessed with a
multiple-item scale developed by the research team,
which measured global perceptions of stress and
captured occupation-specic stress that is particu-
larly relevant to physicians. The survey included 15
items from the Perceived Stress Scale and 25 items
from the Personal and Organizational Quality Assess-
ment–Revised (POQA-R) questionnaire for anxiety,
anger, physical symptoms of stress and work-related
time pressures. The nal 40-item instrument was vali-
dated through conrmatory common factor analysis.
Pre-intervention data was compared to data collected
28 and 56 days later.
The analysis of the data at day 28 showed that the
mean stress score declined signicantly for the inter-
vention group (change –14.7, standard deviation [SD]
23.8; p = 0.013) but not for the control group (change
–2.2, SD 8.4; p = 0.30). The difference in mean score
change between the groups was 12.5 (p = 0.048). The
lower mean stress scores in the intervention group
were maintained during the trial extension to day 56.
After the assessment at day 28 the control group re-
ceived the same intervention, after which mean stress
scores were signicantly lower at day 56 (change –8.5,
SD 7.6; p < 0.001).
The authors concluded that HRV coherence training
along with practice of a self-regulation technique may
be a simple and effective stress-reduction strategy
for physicians.
Medical Error Reductions
Another study conducted with a large chain of retail
stores that had in-store pharmacies employing 220
pharmacists across multiple locations found a re-
duction in medical errors ranging from 40% to 71%,
depending on the store location.[292]
Chapter 8: Health Outcome Studies
66
© Copyright 2015 HeartMath Institute
Science of the Heart
Outcome Studies in Education
Growing evidence of the tremendous benets to be gained from learning to self-regulate emotions and stress
at an early age is becoming increasingly apparent. In today’s fast-paced society there is mounting pressure
on children to achieve and excel in school at younger and younger ages. Today’s children, however, experience
considerably greater stress in their lives, shouldering far greater responsibilities and emotional burdens than
youngsters their age did even as few as 10 years ago. Many are part of deteriorating families or households in
which parents are rarely home and the responsibility for their and their younger siblings’ care has fallen largely to
them. The majority of these children nd little more comfort or security at school, where they often fear becoming
victims of bullying and violence and feel pressured to engage in sex or consume drugs and alcohol. Increasing
media reports of extreme episodes of violence in schools recently have raised public awareness of children’s
deteriorating emotional health and underscored the need for more effective solutions to resolve these issues.
________________________________
“We are educated in school that practice
precedes effectiveness, whether in reading,
writing, computers, or whatever.
We are rarely taught how to practice care,
compassion, appreciation or love
—essential for family balance.
– Doc Childre
_________________________________
Our educational systems continue to focus on honing
children’s cognitive skills from the moment they enter
the kindergarten classroom. Virtually no emphasis is
placed on educating children on managing the inner
conicts and unbalanced emotions they bring with
them to school each day. As new concepts such as
“social and emotional intelligence” become more
widely applied and understood, more educators are
realizing that cognitive ability is not the sole or neces-
sarily the most critical determinant of young people’s
aptitude for ourishing in today’s society. Prociency
in emotional management, conict resolution, com-
munication and interpersonal skills is essential for
children to develop inner self-security and the ability to
effectively deal with the pressures and obstacles that
will inevitably arise in their lives. Moreover, increasing
evidence is illuminating the link between emotional
balance and cognitive performance. Growing numbers
of teachers agree that children come to school with so
many problems that it is dicult for them to focus on
complex mental tasks and the intake of new informa-
tion, skills that are essential for effective learning. A
substantial body of evidence exists that clearly shows
when children also learn social and emotional skills,
lifelong benets that cross domains and expand the
mind’s capacities can be obtained.
________________________________
“Some students came to me having memorized
the denition of peace, for instance, and
they had no idea what it really meant –
especially for them personally.
–Edie Fritz, Ed.D., educational psychologist
_________________________________
In 1940, the top problems in American public
schools, according to teachers, were: talking
out of turn, chewing gum, making noise, run-
ning in the halls and littering. In 1990, teachers
identied the top problems as drug abuse,
alcohol abuse, pregnancy, suicide and robbery
and assault.[293]
CHAPTER 9
67
© Copyright 2015 HeartMath Institute
Since 1978, assaults on teachers have risen
700%.[294]
One youth in six, between the ages of 10 and
17, has seen or knows someone who has been
shot.[295]
A study found that in a group of neglected
children, the cortex, or thinking part of the
brain, was 20% smaller on average than in a
control group.[296]
Positive emotions have been found to pro-
duce faster learning and improved intellectual
performance. B. Fredrickson. Rev Gen Psychol.
1998; 2(3)
In a sample of youth ages 7 to 11 years old in
the Pittsburgh, Pa. area, over 20% were deter-
mined to have a psychiatric disorder.[297]
Only 37% of youth report feeling a sense of
personal power, and half feel that their life has
a purpose.[298]
Since 1960 the rate at which teenagers com-
mit suicide has more than tripled. Suicide is
now the second leading cause of death among
adolescents.[299]
The more teenagers feel loved by their parents
and comfortable in their schools, the less likely
they are to have early sex, smoke, abuse alco-
hol or drugs or commit violence or suicide.[300]
Self-Regulation and Reduced Test
Anxiety and Increased Test Scores
A grant from the U.S. Department of Education pro-
vided funding for a randomized controlled study of
980 10th-grade students in two large high schools.
The TestEdge National Demonstration Study (TENDS)
was conducted by researchers at HeartMath Institute
in collaboration with faculty and graduate students
in Claremont Graduate University’s School of Edu-
cational Studies. The study’s primary purpose was
to investigate the ecacy of the TestEdge program
in reducing stress and test anxiety and improving
emotional well-being, psychosocial functioning and
academic performance in public school students.
This involved determining the magnitude, correlates
and consequences of stress and test anxiety in a large
sample of students and investigating the degree to
which the TestEdge program could benet students in
an experimental group, compared to those in a control
group. A second programmatic purpose was to char-
acterize the implementation of the program in relation
to its receptivity, coordination and administration in a
wide variety of school systems with diverse cultural,
administrative and situational characteristics.[110, 301]
The study tested two major hypotheses. The rst is
that competence in the emotion self-regulation skills
taught in the TestEdge program would result in signi-
cant reductions in test anxiety, which, in turn, would
generate a corresponding improvement in academic
and test performance. Secondly, as a result of the
improvement in student self-regulation skills, it was
hypothesized there would be improvements in stress
management, emotional stability, relationships, overall
student well-being, and in classroom climate, organi-
zation and function. To investigate these hypotheses,
two studies were conducted, each with different re-
search objectives and designs.
Primary Study
The primary study focused on an in-depth investiga-
tion of the entire 10th-grade populations at two large
California high schools. One high school was ran-
domly selected as the intervention school, while the
other served as the control school. This was designed
as a quasi-experimental, longitudinal eld study in-
volving pre- and post-intervention measures within a
multimethods framework. Extensive quantitative and
qualitative data were gathered using a questionnaire
developed and validated for the study, interviews and
structured observation, and student test scores from
California standardized tests – the California High
School Exit Examination (CAHSEE) and the Califor-
nia Standards Test (CST). Altogether, 980 students
participated in the primary study, of which 636 (53%
male, 47% female) were in the experimental group and
344 (40% male, 60% female) were in the control group.
Chapter 9: Outcome Studies in Education
68
© Copyright 2015 HeartMath Institute
Science of the Heart
The TestEdge program was taught by English teachers
over one semester for approximately four months. In
the program, students learned and practiced specic
emotion-management techniques to aid them in more
effectively handling stress and challenges, both at
school and in their personal lives. They also were
taught how to apply these techniques to enhance
various aspects of the learning process, including
test preparation and test-taking. Both the student and
teacher programs included use of the Freeze-Framer
(now emWave Pro) technology, a heart-rhythm coher-
ence feedback system designed to facilitate acquisi-
tion and internalization of the self-regulation skills
that were taught.
Across the whole sample at baseline, 61% of all stu-
dents reported (Spielberger test-anxiety inventory)
being affected by test anxiety, with 26% experiencing
high levels of test anxiety often or most of the time.
Twice as many females as males experienced high
levels of test anxiety. There was a strong negative re-
lationship between test anxiety and test performance;
students with high levels of test anxiety scored, on
average, 15 points lower on standardized tests in both
mathematics and English-language arts (ELA) than
students with low test anxiety (Figure 9.1). A multiple
regression analysis found that affective mood mea-
sures accounted for the wide variance between stu-
dent test performance on both the CST and CAHSEE
English-language arts exams and Test Anxiety Inven-
tory – global scale (23% versus ~13%, respectively).
Positive feelings and prosocial behaviors were found
to have positive effects on test performance, while
strongly negative feelings and antisocial behaviors
had negative effects.[302] Taken as a whole, these nd-
ings are sobering and justify the concern that student
test anxiety and emotional stress may signicantly
jeopardize assessment validity and therefore may
constitute a major source of test bias.
There was a signicant reduction in the mean level
of test anxiety. Of those students at the intervention
school who had reported being affected by test anxiety
at the beginning of the study, 75% had reduced levels
of test anxiety by the end of the study. This reduc-
tion in test anxiety also was evident in more than
three-quarters of all classrooms, and it was observed
throughout the academic ability spectrum, from
high test-performing classes to low test-performing
classes.
Test Anxiety-Global
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Low Med High
Test Anxiety Level
TAI Scale Score
CAHSEE Mathematics
375
380
385
390
395
400
405
Low Med High
Test Anxiety Level
Test Score
CAHSEE English -
Language Arts
375
380
385
390
395
400
405
Low Med High
Test Anxiety Level
Test Score
Figure 9.1. Baseline test anxiety, measured by the Test Anxiety Inventory (TAI) – global scale score and California High School
Exit Examination (CAHSEE) scores in English-language arts and mathematics have been classied into three approximately
equal-sized groupings of students with low, medium, and high test anxiety scores. A strong, statistically signicant (p < 0.001)
negative relationship is clearly apparent between mean level of test-anxiety and mean performance on the standardized tests:
As test anxiety increases, test performance decreases.
69
© Copyright 2015 HeartMath Institute
After the TestEdge program was provided to the stu-
dents in the intervention school, there was strong,
consistent evidence of a positive effect from the
intervention on these students, compared to those
in the control school. The reduction in test anxiety
was associated with significant improvements in
social and emotional measures (Figure 9.2), includ-
ing reductions in negative affect, emotional discord
and interactional difculty, and an increase in positive
class experience. In four matched-group comparisons
(involving subsamples of 50 to 129 students per
grouping), there was a signicant increase in test per-
formance in the experimental group over the control
group, ranging on average from 10 to 25 points. In two
of these matched-group comparisons, this signicant
increase in test performance was associated with a
signicant decrease in test anxiety in the experimental
group (Figure 9.3).
*
*
*
*
***
***
***
1.5
2.0
2.5
3.0
Test
Anxiety-
Global
Test
Anxiety-
Worry
Test
Anxiety-
Emotional
Positive
Class
Experience
Negative
Affect Emotional
Discord Interactional
Difficulty
Survey Score
Experimental Group (N=488) Control Group (N=261)
Error bars = SEM
Figure 9.2. Results of an ANCOVA of pre– and post-intervention changes in measures of test anxiety (global scale, worry component,
and emotionality component) and social and emotional scales (positive class experience, negative affect, emotional discord, and
interactional difculty) showing signicant differences between the intervention and control schools. *p < 0.05, ***p < 0.001.
*
396
400
404
408
412
416
CST ELA Scale Score
Experimental (N=69) Control (N=60)
*
1.0
1.2
1.4
1.6
1.8
2.0
2.2
2.4
Test Anxiety - Global Score
Math Group 1*
*
332
336
340
344
348
352
356
CST ELA Scale Score
Experimental (N=49) Control (N=27)
*
1.0
1.2
1.4
1.6
1.8
2.0
2.2
2.4
2.6
Test Anxiety - Global Score
White Females Regular Classes
Test Anxiety Test Performance
Test Anxiety Test Performance
* Students who took 9th grade Geometry & 10th grade Algebra 2
Figure 9.3. ANCOVA results for two subsamples from the intervention and control schools matched on sociodemographic
factors (White females in average academic-level classes) and ninth-grade math-test performance (Math Group 1), respectively.
For these matched-group comparisons, signicant reductions in test anxiety in conjunction with signicant improvements in
test performance (California Standards Test – English-language arts) were observed in the experimental group, compared to the
control group. *p < 0.05.
Chapter 9: Outcome Studies in Education
70
© Copyright 2015 HeartMath Institute
Science of the Heart
________________________________
“As annual testing becomes a regular part
of our educational system through the
No Child Left Behind Act and other state
requirements, it is important that when we test
students on their mastery of a subject, we are
truly getting accurate results.
The program developed by HeartMath Institute
to reduce test-related anxiety shows great
potential for helping students achieve success.
– Rep. Ralph Regula (R-OH)
_________________________________
Student participants describe how they apply
HeartMath skills in various areas of their lives:
“I use HeartMath every day before math class.
This helps me understand the concepts and grasp
them more easily.
“HeartMath has obviously helped in my algebra II
class. On the last test, using HeartMath, I scored
a 97%. It really calmed me down and opened my
mind to clearer thinking.
“Working at Coney Island, I’m around people
all the time; being an assistant manager, the
questions, concerns and complaints all come
to me. In order to answer them or handle the
situation without taking it personally, I use
HeartMath. It’s helped calm my nerves a lot.
“Sometimes during sports activities I get mad
at myself and do very badly. One time I used
HeartMath and I let all of my stress go and
just had fun. In the end, I performed better than
I expected.
“I have used HeartMath during band. I hate the
feeling of having to play a hard part in front of
the whole band by myself. I get so nervous
sometimes that my hands shake and my mind
goes blank. … Using HeartMath, I have seen a
signicant improvement in my playing alone in
front of people.
“I use HeartMath during any stressful encounter
I have, whether at home, school, with my parents
or with friends. Anytime I get frustrated or upset, I
try to practice (HeartMath techniques) and focus
from head to heart.
“(One) time, I was taking a test in Chemistry, and
I could not remember the equation for the test.
I had three minutes left and I used one of those
minutes to do HeartMath. … I ended up getting a
90% on the test and brought my chem grade up.
“(One) instance was a presentation in English
class. I am a shy, solitary person and I sometimes
get very stressed with presentations. However, I
used what I learned from HeartMath and was able
to present my topic efciently.
“Whenever I email or write my boyfriend, who
recently left to work in Utah over the summer,
I use HeartMath to calm down and say what I
want to say without sounding angry, upset
– and (not) panic.
Physiological Study Findings
In addition, a physiological substudy was conducted
on a randomly stratied sample of students from
both schools. Utilizing measures of heart rate vari-
ability (HRV), this controlled laboratory experiment
investigated the degree to which students had learned
the skills taught in the TestEdge program using an
objective measurement of their ability to shift into
the physiological coherence state before taking a
stressful test.[110]
In a controlled experiment simulating a stressful
testing situation, students from the intervention and
71
© Copyright 2015 HeartMath Institute
control schools (N = 136) completed a computerized
version of the Stroop color-word conict test (a stan-
dard protocol used to induce psychological stress),
while continuous heart rate variability recordings
were gathered. For the pre-intervention administration
of the experiment, after a resting HRV baseline had
been collected, students were instructed to mentally
and emotionally prepare themselves to perform an
upcoming challenging test and activity, after which
they participated in the Stroop test. They also were
told if they performed well on the test, they would be
given a free movie pass. The same procedures were
used in the post-intervention assessment.
Results from the post-intervention physiological
experiment:
> The HRV data indicated students who had received
the TestEdge program had learned how to better
manage their emotions and to self-activate the
physiological coherence state under stressful
conditions during the stress-preparation segment
of the protocol (Figure 9.4).
> The ability to self-activate coherence noted above
was associated with signicant reductions in test
anxiety and corresponding improvements in mea-
sures of emotional disposition.
> For students matched on baseline test scores, the
capacity to self-activate coherence was associ-
ated with a reduction in test anxiety as well as an
improvement in test scores in the experimental
group (Figure 5.1). This nding is consistent with
the results for students in the larger study.
> Students in the experimental group also exhibited
increased heart rate variability and heart-rhythm
coherence during the resting baseline period in
the post-intervention experiment – even without
conscious use of the self-regulation techniques.
This suggests that through consistent use of the
coherence-building tools over the study period,
these students had internalized their benets,
thus instantiating a healthier, more harmonious
and more adaptive pattern of psychophysiological
functioning as a new set-point or norm.
Pre
Post
***
1.0
2.0
3.0
4.0
5.0
Ln(Coherence Ratio)
Pre–Post Stress Preparation Phase
Coherence Measure by Intervention Status
Experimental
Group Control
Group
Figure 9.4. These data are from the physiological study, a
controlled experiment involving a random stratied sample
of students from the intervention and control schools (N =
50 and 48, respectively). These graphs quantify heart-rhythm
coherence, the key marker of the psychophysiological
coherence state, during the stress-preparation phase of the
protocol. Data are shown from recordings collected before
and after the TestEdge program. The experimental group
demonstrated a signicant increase in heart-rhythm coherence
in the post-intervention recording when they used one of
the self-regulation techniques to prepare for the upcoming
stressful test – compared to the control group. ***p < 0.001.
Qualitative Findings:
To supplement the quantitative data, the study gath-
ered observations of student classroom interactions
in the two schools and conducted structured inter-
views with teachers. The pre- and post-observational
ndings were broadly consistent with the ndings
from the quantitative analysis:
> More positive changes were observed in the so-
cial and emotional environment and interaction
patterns in the classrooms of the experimental
school, while more negative changes were ob-
served in the control school over the course of
the semester.
> Students at the experimental school exhibited
reduced levels of fear, frustration and impulsivity.
They also exhibited increased engagement in class
activities, emotional bonding, humor, persistence
and empathetic listening and understanding.
> Most teachers acknowledged in interviews that
their students came to school emotionally unpre-
pared to learn, but they felt their own educational
Chapter 9: Outcome Studies in Education
72
© Copyright 2015 HeartMath Institute
Science of the Heart
training did not equip them with the requisite skills
to effectively manage their personal stress or to
help their students manage their stress. Teachers
were supportive of integrating emotion-manage-
ment instruction into educational curricula. Most
reported experiencing personal benets as well
as observing positive changes in their students’
behavior as a result of the intervention program.
Secondary Study
The secondary study consisted of a series of qualita-
tive investigations to evaluate the accessibility, recep-
tivity, coordination and administration of the program
across elementary, middle and high schools and in
school systems with diverse ethnic, cultural, socioeco-
nomic, administrative and situational characteristics.
We employed a case-study approach to evaluate the
implementation of the TestEdge program in nine
schools in eight states (California, Delaware, Florida,
Ohio, Maryland, Texas, Wisconsin, and Pennsylvania).
Age-appropriate versions of the TestEdge program
were delivered to selected classrooms, covering the
third through eighth and 10th grades.
Observational and interview data were gathered to
provide information on best practices and potential
diculties when implementing interventions such as
TestEdge in widely diverse school settings.
Major Findings from the Secondary Study
Evaluation of the implementation case studies of
the TestEdge program, conducted in selected class-
rooms at various grade levels across different states,
produced a number of notable results and largely cor-
roborated the ndings from the primary study:
> In teacher interviews, the lack of emotion- and self-
management education for students was seen as
a signicant obstacle to learning and academic
performance. Most teachers described positive
changes in students’ attitudes, behaviors, test
anxiety and academic performance, and attributed
these to the TestEdge program. They also felt that
the tools and skills that were learned would have
a positive impact on their students’ future social,
emotional and academic development.
> Most teachers reported that the program provided
substantial benets in their personal and profes-
sional lives.
> In general, the program’s implementation was more
successful when there were several teachers at
the same grade level teaching it and when teach-
ers were able to internalize the use of the tools in
their own lives.
> Major challenges to successful program imple-
mentation included inadequate class time; logis-
tical problems encountered with school adminis-
tration; and securing the support of the principal
and other school administrators to foster teacher
commitment.
Elementary School Case Study:
A case example of highly successful implementation
of the TestEdge program was provided by an in-depth
study conducted at the third-grade level in a Southern
California elementary school. Several notable ndings
emerged from the study:
> Large increases in state-mandated test scores
were observed, which far exceeded academic tar-
gets for the year. As a result, student prociency
grew from 26% to 47% in English-language arts
and from 60% to 71% in mathematics.
> Corresponding emotional and behavioral improve-
ments also were observed among students in the
classrooms.
> The success of implementation was largely the
result of the enthusiastic support provided by the
school’s principal and key teachers and adminis-
trators.
Conclusion
Overall, the evidence from this rich combination of
physiological, quantitative, and qualitative data in-
dicates that the self-regulation skills and practices
taught in the TestEdge program led to a number of
73
© Copyright 2015 HeartMath Institute
important successes. It is our hope that the results
of this research will have an impact on policies regard-
ing the importance of integrating stress and emotion
self-management education into school curricula for
students of all ages. By introducing and sustaining
appropriate programs and strategies, it should be
possible to signicantly reduce the stress and anxiety
that impede student performance, undermine teacher-
student relationships and cause physiological and
emotional harm. Such programs have the promise
of increasing the effectiveness of our educational
system and, in the long-term, boosting the academic
standing of the United States in the international
community.
Evaluation of HeartMath Program with
Schoolchildren in West Belfast
A study was conducted in Belfast, Ireland to inves-
tigate the efficacy of a HeartMath program as a
means of improving student emotion self-regulation
and associated improvements in emotional stability,
relationships and overall student well-being.[303] Seven
schools were chosen for the study: three were primary
schools (n = 122) and four were post-primary schools
(n = 121). Two or three classes from each school
participated in the study. Each class participated in
a one-day interactive program in which they learned
how to use the HRV coherence system (emWave Pro)
and was taught an emotion self-regulation technique.
The students and teachers also were provided with an
audio CD called “Journey to my Safe Place” to lead
them through a self-regulation exercise at later times.
Teachers were encouraged to allow the students to
use the games on the emWave once or twice weekly,
as time permitted. The outcome measure was the
Strengths and Diculties Questionnaires (SDQ) for
ages 4 to 16; these were completed pre- and post-
intervention by the teachers.
Based on the SDQ scales, the primary students
showed a statistically signicant reduction in emo-
tional problems (51%); conduct problems (43%);
hyperactivity (40%); and a signicant improvement in
relating to peers (50%). According to the scales, post-
primary students had signicant reductions in hyper-
activity (12%), emotional problems (9%) and conduct
problems (9%), and they showed (27%) improvement
in relating to peers. As expected, the primary children
benetted more than post-primary students, and the
authors suggest this may be the result of better adher-
ence to utilizing the skills, which are easier to reinforce
in primary-school students because they are in the
same classroom each day. In contrast, the students
in the post-primary schools move from class to class
throughout the day, so it was more dicult to set up a
routine to support the intervention. In addition, most
of the primary-school classes began the study several
weeks before the post-primary classes, which gave
them more time to plan how the program would be
integrated into their classes.
Self-Regulation for Promoting
Development in Preschool Children
The importance of children learning effective social
and emotional skills at an early age cannot be overes-
timated. A large body of research clearly shows that
learning how to process and self-regulate emotional
experience in infancy and early childhood not only fa-
cilitates neurological growth, but also determines the
potential for subsequent psychosocial and cognitive
development. Conversely, the inability to appropriately
self-regulate feelings and emotions can have devastat-
ing long-term consequences in a child’s life, impeding
development and often resulting in impulsive and ag-
gressive behavior, attentional and learning diculties
and an inability to engage in prosocial relationships.
Furthermore, this early deciency is associated with
later-forming psychosocial dysfunction and pathology
that not only robs individuals of a fullling life, but also
results in an enormous cost to our society.[80]
The HeartMath Institute developed a program called
Early HeartSmarts® (EHS) specically intended to
help equip children aged 3 to 6 with the foundational
emotion self-regulation and social competencies
for school. The program trains teachers to guide
children in learning emotion self-regulation and key,
age-appropriate social and emotional skills, toward
a goal of promoting children’s emotional, social,
and cognitive development. The Early HeartSmarts
Chapter 9: Outcome Studies in Education
74
© Copyright 2015 HeartMath Institute
Science of the Heart
program included interactive activities, games and
self-management tools designed to promote chil-
dren’s learning of several key emotional and social
competencies, which in turn are known to promote
psychosocial development. These included:
How to recognize and better understand basic
emotional states.
How to self-regulate emotions.
Ways to strengthen the expression of positive
feelings.
Ways to improve peer relations.
Skills for developing problem-solving.
A study was conducted in the Salt Lake City School Dis-
trict to evaluate the ecacy of the Early HeartSmarts
program.[304] The study was conducted over the school
year using a quasi-experimental longitudinal eld
research design with three measurement moments
(baseline and pre- and post-intervention panels). Chil-
dren in 19 preschool classrooms at 19 schools were
divided into intervention and control group samples
(N = 66 and 309, respectively; mean age = 3.6 years).
Classes in the intervention group were selected by
the district to target children of lower socioeconomic
and ethnic minority backgrounds. The Creative Cur-
riculum Assessment (TCCA), a teacher-scored, 50-item
instrument, was used to measure student growth in
four areas of development: social/emotional, physical,
cognitive and language development.
Teachers delivered the program to their students
throughout the second half of the school year. A key
element of the program was learning and practicing
two simple HeartMath emotion-shifting tools: Shift
and Shine and Heart Warmer.
Overall, results provided compelling evidence of the
ecacy of the EHS program increasing total psycho-
social development and each of the four develop-
ment areas measured by the Creative Curriculum
Assessment: The results of a series of ANCOVAs
found a strong, consistent pattern of large, signicant
differences on the development measures favoring
preschool children who received the EHS program
over those in the control group (see Figure 9.5). From
the adjusted means on the ve development scales,
a signicant difference with a large effect size was
observed favoring the intervention group on the total
development scale (ES 0.81, p < 0.001), and on each
of the social/emotional development (ES 0.97, p <
0.001), physical development (ES 0.79, p < 0.001), cog-
nitive development (ES 0.55, p < 0.01), and language
development (ES 0.73 p < 0.001) scales. And at the
subcomponent level (right-hand graph in Figure 9.5),
the intervention group demonstrated a statistically
signicant improvement in all 10 constructs, eight of
which showed differences that were large in terms of
effect size. The magnitude of development observed
for the intervention-group children is particularly strik-
ing, considering that initial measurements indicated
that at the beginning of the study, they started with
a signicant development handicap relative to their
peers in the control group. After participating in the
EHS program, they had surpassed the control group’s
development growth by the end of the study. A further
important nding, from an analysis of demographic
factors, was that the program was effective in pro-
moting development in children across all the socio-
demographic categories investigated: males, females,
Hispanic, Caucasian, free lunch (an indicator of low
socioeconomic status) and no free lunch.
An important point to emphasize is that these results
are for preschool children, who are very young, and
96% of them were 3.0 to 4.0 years old. It is both strik-
ing and remarkable that children as young as 3 can
begin to learn and practice the emotion self-regulation
skills, which appears to promote their development
across a wide range of categories. Given that the
age range from 3 to 6 years is a period of acceler-
ated neurological growth and development, it is likely
that the learning and sustained use of these skills
and practices during this important developmental
period will readily instantiate a new set point in a
young child’s nervous system for an optimal pattern
of emotion self-regulation and healthy social func-
tion, thereby signicantly boosting the development
trajectory of future prosocial behaviors and academic
achievement.
75
© Copyright 2015 HeartMath Institute
L
***
L
***
L
**
L
***
0
5
10
15
20
25
30
35
40
45
Social/Emotional Development Score
Physical Development Score
Cognitive Development Score
Language Development Score
Intervention Group (N=65) Control Group (N=301)
L
***
L
***
L
**
L
***
L
***
L
***
M
***
M
**
L
***
L
***
0
5
10
15
20
25
Sense of Self
Responsibility for Self and Others
Prosocial Behavior
Gross Motor
Fin e Motor
Learning and Problem Solving
Log ical T hin king
Representation and Symbolic Thinking
Listening and Speaking
Reading and Writing
Significance: * p < 0.05, ** p < 0.01, *** p < 0.001
Effect s ize:
M
0.30 - 0.49 Moderate,
L
0.50 Large
L
***
0
20
40
60
80
100
120
140
Total
Development
Score
Figure 9.5. Adjusted means showing results of ANCOVA of intervention effects on development measures comparing intervention
and control groups.
Reduced Burnout in College Students
Dr. Ross May and colleagues at Florida State Univer-
sity have found that the psychophysiological function-
ing underlying school burnout is of particular impor-
tance. Their research has shown student burnout is
associated with increased markers of cardiovascular
risk and poor academic performance (GPA).[305, 306] They
suggest that because school burnout is associated
with increased cardiac risk, it should be recognized as
a potential public health issue and a cause for concern
for university ocials. This is especially true because
cardiovascular disease (CVD), including hyperten-
sion, coronary heart disease, heart failure, peripheral
artery disease and stroke, is the most salient cause of
death in the United States and the rest of the world.
The cardiovascular responses seen from individuals
suffering from higher levels of burnout have been
identied as risk factors for the future development
of cardiovascular disease.[307-309] They also have dem-
onstrated that school burnout is a stronger predictor
of GPA than anxiety and depression.
May and his colleagues conducted a study comparing
the effects of training in HeartMath self-regulation
techniques, supported by HRV coherence training,
with high-intensity aerobic training (HIIT); both types
of training were intended to ameliorate school burnout
in undergraduate students. A total of 90 participants
(freshman year, mean age = 18.55, SD = 0.99, 82% fe-
male) were randomly assigned to one of the following
three groups: one that received the HeartMath Building
Personal Resilience program, which included learning
self-regulation techniques and HeartMath’s computer-
based HRV coherence training devices (emWave),
high-intensity aerobic training and a no-intervention
control. All of the groups were evaluated for cognitive,
psychological and cardiovascular functioning before
and after a four-week intervention period. The ethnic
composition of the sample was 70% Caucasian, 7%
African American, 13% Hispanic, 7% Asian and 3%
undisclosed ethnicity.
All participants completed a physical health history
questionnaire, the School Burnout Inventory (SBI),
Center for Epidemiologic Studies Depression Scale
(CES-D), and the State-Trait Anxiety Inventory (STAI),
and a self-reported sleep quality questionnaire.
In addition, academic absenteeism (how many
classes were missed over the semester) and GPA
Chapter 9: Outcome Studies in Education
76
© Copyright 2015 HeartMath Institute
Science of the Heart
were assessed. Cognitive functioning was assessed
with computerized working-memory span measure
versions of the common reading and operation work-
ing memory span tasks.[310, 311] The span tasks require
participants to remember target letters while perform-
ing a concurrent reading comprehension (reading
span) or arithmetic task (operation span). The number
of targets in a trial set varied between two and ve,
with three trials of each size for each of the tests.
Physical tness with a stationary bike test and V02
max and cardiovascular functioning were assessed
by measures of aortic hemodynamics, beat-to-beat
blood pressure, and heart rate variability.
The HeartMath resilience training and HRV coherence
sessions were conducted at the university wellness
center by trained student instructors three times per
week over a four-week period. Each student practiced
shifting and sustaining heart-rhythm coherence while
using an emWave device and was encouraged to use
the techniques and device on a regular basis to help
them improve their self-regulation skills and physi-
ological and psychological balance. The high-intensity
interval training (HIIT) comprises brief bursts of in-
tense exercise separated by short periods of recovery.
This method of exercise is a time-ecient stimulus to
induce physiological adaptations normally associated
with continuous moderate-intensity training.[312] As
few as six sessions of HIIT over two weeks has been
shown to increase muscle oxidative capacity to the
same extent as a continuous moderate-intensity train-
ing protocol that requires an approximately threefold
greater time commitment and approximately ninefold
higher training volume.[313] The HIIT training sessions
were conducted at the university wellness center by
trained instructors three times per week over four
weeks. The control group visited the wellness center
to report their normal daily activities for the duration
of the study. Participants were encouraged to not
change their normal daily routines.
In comparison to HIIT and control, the HeartMath
group participants had significant improvements
in academic success and concentration and sig-
nicant decreases in test anxiety and absenteeism
(Figure 9.6).
Figure 9.6 shows the data for the three groups for academic success, test anxiety, concentration and absenteeism from classes
over the semester. Data are mean and 95% CI. * = p <.05 HeartMath vs. HIIT posttest, + = p <.05 HeartMath vs. Control, a = p <.05
HeartMath pretest vs. HeartMath posttest, b = p <.05 HIIT pretest vs. HIIT posttest, c = p <.05 Control pretest vs. Control posttest.
The HeartMath group also was the only group to show a signicant reduction in school burnout from the pretests
to posttests (Figure 9.7) and signicant improvements in the cognitive functioning assessments of reading and
operational span working memory capacity from the pretests to posttests (Figure 9.8 and 9).
77
© Copyright 2015 HeartMath Institute
Figure 9.7 shows the pre- and post-data for the three
groups for school burnout. Data are mean and 95% CI
a = p <.05 HeartMath pretest vs. HeartMath posttest.
Figure 9.8 shows the pretest and posttest data for the three
groups for reading working memory. Data are mean and 95% CI
a = p <.05 HeartMath pretest vs. HeartMath posttest.
Figure 9.9 shows the pretest and posttest data for the three
groups for math working memory. Data are mean and 95% CI
a = p <.05 HeartMath pretest vs. HeartMath posttest.
In terms of cardiovascular functioning, the HeartMath
group showed signicantly decreased brachial and
aortic blood pressure, and both the HeartMath and
HIIT groups had signicantly decreased heart rate
from pretest to posttest (Figure 9.10, 11 and 12). The
HRV metrics showed that the normalized LF power
was signicantly lower in the post-assessment mea-
sures, compared to the pre-intervention measures,
and HF power was signicantly increased in all three
groups (Figures 9.13 and 14). In addition, the HIIT
group was the only group to show signicantly im-
proved VO2 max.
Figure 9.10 Brachial systolic blood pressure (BSBP) data
for the three groups. Data are mean and 95% CI. a = p <.05
HeartMath pretest vs. HeartMath posttest.
Figure 9.11 Aortic systolic blood pressure (ASBP) data for the
three groups. Data are mean and 95% CI a = p <.05 HeartMath
pretest vs. HeartMath posttest.
Figure 9.12 Heart-rate data for the three groups. Data are
mean and 95% CI. * = p <.05 HeartMath vs. HIIT, b = p <.05
HIIT pretest vs. HIIT posttest.
Chapter 9: Outcome Studies in Education
78
© Copyright 2015 HeartMath Institute
Science of the Heart
Figure 9.13 Normalized low frequency power data for the
three groups. Data are mean and 95% CI.
a
= p <.05 HeartMath
pretest vs. HeartMath posttest,
b
= p <.05 HIIT pretest vs. HIIT
posttest,
c
= p <.05 Control pretest vs. Control posttest.
Figure 9.14 Normalized high frequency power data for the
three groups. Data are mean and 95% CI.
a
= p <.05 HeartMath
pretest vs. HeartMath posttest,
b
= p <.05 HIIT pretest vs. HIIT
posttest,
c
= p <.05 Control pretest vs. Control posttest.
Coherent Learning: Creating High-level
Performance and Cultural Empathy
From Student to Expert
Nursing schools are charged with graduating nurs-
ing students who reect the race and ethnicity of the
communities those schools serve. In 1998, 19 Native
American students were admitted to the University
of Oklahoma College of Nursing. Only 12 had gradu-
ated two years later. The rate of attrition for Native
American nursing students averaged 57% between
1997 and 2001, compared to the overall attrition rate
of approximately 9%.
The OU College of Nursing identied staff members
to become certied in a HeartMath program in 2002.
The program was implemented starting in 2003.
Participation in the program was voluntary for the
rst year, but it became part of the new-student ori-
entation the next year. Training was offered monthly
for students and faculty and was available to every
student. Laboratory computers were equipped with
the HRV coherence training technology to support the
self-regulation skills so students could practice during
school hours. Several faculty members also provided
student mentoring and practiced with students in their
oces at students’ request. Many faculty members
gave short sessions for the students on how to do the
self-regulation techniques before taking tests.
Although only Native American students are reported
here, students from all ethnicities and races reported
benets. Based on test results for all students, it was
determined that practicing the HeartMath techniques
increased test scores by an average of 17 points.
Following implementation of the HeartMath self-
regulation tools in 2003, the average attrition rate for
Native American nursing students between 2003 and
2008 was 37%, compared to the 57% attrition rate in
the 1997-2001 period. During this time, requirements
for admission and graduation became more stringent
and required increased testing. From the start of the
program through 2006, the overall attrition rate for the
school dropped from the 9% reported in 2001, varied
from 3% or less. Use of HeartMath while in the school
helped decreased the attrition rate by about 35% for
Native American students from 2003 to 2008.
Students reported increased condence in their test-
taking abilities and reported fewer physical health
issues, which they attributed to the regular practice
of the self-regulation skills they learned.
In addition, the Native American nursing students
using the stress-reducing practices demonstrated
improved test-taking and perceived physical health
and higher graduation rates than those who did not
use them.[314]
Improving Learning and Math
Prociency in College Students
A major challenge in our current educational system
is the signicant number of students entering col-
lege who do not meet the basic minimum academic
requirements for enrolling in college-level courses.
79
© Copyright 2015 HeartMath Institute
These students must take remedial courses in core
academic subjects before they are ready to enter
regular college classes. Personnel at the University
of Cincinnati Clermont College (UCCC) have observed
that as many as 92% of incoming rst-year college
students score below standards for college-level
mathematics. As a result, students have diculty suc-
ceeding in their required mathematics courses. UCCC
and the Greater Cincinnati Tech Prep Consortium have
formed a partnership to help solve this problem, with
the goal of reducing the need for remediation in math.
Working with this program, UCCC professors Drs.
Michael Vislocky in mathematics and Ron Leslie in
psychology pioneered a new approach.[315]
They integrated HeartMath’s self-regulation tech-
niques and heart-rhythm coherence feedback tech-
nology into college prep readiness programs in math.
The goal of these programs was to reduce high school
students’ anxiety related to learning math and taking
high-stakes tests and thereby improve students’ learn-
ing, comprehension and retention.
________________________________
“Lots of people are afraid of math.
Learning to center in stressful situations can
help these students perform better on tests,
and it also opens up their life choices.
So many people will switch majors just to
avoid a specic math class.
Dr. Michael Vislocky
professor of mathematics
University of Cincinnati Clermont College
_________________________________
The following elements were included in the train-
ing: 1) Discussion of the physiology of emotions. 2)
Discussion of core values and engaging students in
experiences that allowed them to practice sharing
heartfelt emotions emerging from their core values.
3) Practice moving from the state of thinking about
positive emotional experiences to actually experienc-
ing those emotions. 4) Gaining self-awareness of
emotional shifts. 5) Working in small groups to build
a sense of community in order to become comfortable
generating and sharing positive emotions. The overall
goal of this instruction was to introduce students to
the relationship between emotions and cognitive per-
formance. To assess changes in math performance,
each class of students took the Compass college
placement test in mathematics at the beginning and
end of the three-week program.
Heart-rhythm coherence feedback using the Freeze-
Framer (now called emWave Pro) while simultane-
ously working on math problems was a key element
of the program. In these sessions, students were
able to observe their reactions to dicult problems,
as reected in the HRV feedback, thereby gaining
more insight into their emotional responses and how
to self-regulate them. They practiced self-activating
coherence and using their intuition to nd ways to
solve math problems.
Students were extremely responsive to the program,
and results over the years continuously improved
as the professors discovered new ways to integrate
and sustain students’ use of the self-regulation tech-
niques. In the rst year the professors integrated
HeartMath techniques, they found an average in-
crease of 19% in math scores, which had increased to
24% gains by the third year in Compass test scores,
compared to classes that had not integrated the self-
regulation techniques. These gains were notable given
the program’s short duration and its primary focus
on emotion-management skills rather than on formal
math instruction.
In the fourth year, use of the self-regulation techniques
and other HeartMath practices became fully inte-
grated into the classroom program and produced the
best results of all four years, far exceeding even the
instructors’ expectations. These results are shown in
Figure 9.6, which compares students’ scores on the
Compass college placement test in Algebra before
the program and seven weeks later, after learning and
using the techniques and HRV coherence technology
as an integrated part of their math instruction. The
results showed a signicant (p < 0.001) improvement
with an average increase of 73% in student math scores.
Chapter 9: Outcome Studies in Education
80
© Copyright 2015 HeartMath Institute
Science of the Heart
College Prep Readiness Program COMPASS Test
30
40
50
60
70
80
90
100
110
120
130
COMPASS Test - Total Score
Before After
***
73%
0
20
40
60
80
100
120
140
160
180
200
Before After
COMPASS Test - Total Scores
*** p< .001, N=16
Group Average Score Individual Scores
Figure 9.15. The average and individual student improvements
in scores on the Compass college placement test in algebra
before and seven weeks after learning and using the HeartMath
self-regulation skills and HRV coherence technology as an
integrated part of math instruction. Results show a statistically
signicant (p < 0.001) average increase of 73% in student
scores on the college placement test.
The college prep readiness program was then ex-
panded in following years with the intent of eliminating
the need for students to have to take math remediation
classes. With the support of a high school principal
and math teacher, the program was integrated into an
11th grade math class at a local high school. Guided by
the program instructors, 16 students and their math
teacher learned the tools of the HeartMath System.
The teacher guided the students in using the Heart-
Math techniques as an integral part of the class and
homework. Four Freeze-Framer stations were set up
in the classroom and students practiced using it by
rotating throughout the class period.
________________________________
“I’m ecstatic! High school students are excited
about this program because it gives them an edge
in learning math and in demonstrating their
prociency on tests. Many students who felt
discouraged about their math performance now
feel condent that they can succeed.
– Dr. Michael Vislocky
________________________________
Drs. Vislocky and Leslie observed:
“There was a seamless integration of learning math
and HeartMath infused with the curriculum in the
context of the classroom setting. The teacher inter-
nalized and facilitated the HeartMath process, and
actively engaged students in the learning process.
The teacher got the students personally involved by
giving assignments and journaling their HeartMath
experiences. This provided opportunities to make
continuous improvements based on feedback from
students. Students were condent that their input
was valued and acted upon through adjustments in
the classroom.
Key factors that appear to maximize the success of
the program:
> Committed teacher/facilitator.
> High expectations for student success.
> Managing emotions should take place in the con-
text of the classroom
> Journaling or some mechanism for feedback to
make continuous improvements along the way.
> Begin program at the beginning of the school year.
> Train the teacher/facilitator.
> Students must be provided with ample opportuni-
ties to apply HeartMath tools inside and outside
the classroom.
> Real classroom experiences using HeartMath tools
so individuals realize direct benets.
> Integration of HeartMath in the classroom is impor-
tant for promoting student-to-student interaction.
Drs. Vislocky and Leslie’s work represented the rst
effort we knew of to integrate the HeartMath System
of self-regulation tools directly into a mathematics
learning environment. The ndings provided strong
evidence that the integration of coherence-building
tools and technologies into the instruction of core
academic subjects could be an effective way to en-
hance student learning and academic performance
and to better prepare high school students for entry
into higher education.
81
© Copyright 2015 HeartMath Institute
Social Coherence:
Outcome Studies in Organizations
There are obvious benets to interacting and working with individuals who have a high level of personal co-
herence. When members of any work group, sports team, family or social organization get along well there
is a natural tendency toward good communication, cooperation and eciency. Social and group coherence
involves the same principles as global coherence, but in this context it refers to the alignment and harmonious
order in a network of relationships among individuals who share common interests and objectives, rather than
the systems within the body. The principles, however, remain the same: In a coherent team, there is freedom
for the individual members to do their part and thrive while maintaining cohesion and resonance within the
larger group’s intent and goals. Social coherence is therefore reected as a stable, harmonious alignment of
relationships that allows for the ecient ow and utilization of energy and communication required for optimal
collective cohesion and action.[170]
Chapter 10: Social Coherence: Outcome Studies in Organizations
When individuals are not well self-regulated or are
acting in their own interests without regard to others,
it generates social incoherence. Stressful or dis-
cordant conditions in a given group act to increase
emotional stress among its members and can lead to
social pathologies such as violence, abuse, inecacy,
increased errors, etc.[318] It has become increasingly
clear that the leading sources of stress for adults are
money issues and the social environment at work.
More than 9 in 10 adults believe that stress can con-
tribute to the development of major illnesses such as
heart disease, depression and obesity, and that some
types of stress can trigger heart attacks and arrhyth-
mias. While awareness about the impact stress can
have on emotional and physical health seems to be
present, many working Americans continue to report
symptoms of stress with 42% reporting irritability or
anger, 37% fatigue, 35% a lack of interest, motivation
or energy, 32% headaches and 24% upset stomachs
due to stress.[317]
Job stress is estimated to cost American companies more than $300 billion a year in health costs,
absenteeism and poor performance. In addition, consider these statistics:
40% of job turnover results from stress.[318]
Healthcare expenditures are nearly 50% greater for workers who report high levels of stress.[319]
Replacing an employee costs an average of 120% to 200% of the affected position’s salary.[320]
An estimated 60% of all job absenteeism is caused by stress.[321]
Depression and unmanaged stress are the top two most costly risk factors in terms of medical
expenditures. They increase health-care costs two to seven times more than physical risk
factors such as smoking, obesity and poor exercise habits.[322]
Employees who perceive they have little control over their jobs are nearly twice as likely to
develop coronary heart disease as employees with high perceived job control.[323]
CHAPTER 10
82
© Copyright 2015 HeartMath Institute
Science of the Heart
It also has become apparent that social incoherence
not only inuences the way we feel, relate and com-
municate with one another, it also affects physiologi-
cal processes that directly affect health. Numerous
studies have found that people undergoing social
and cultural changes, or living in situations character-
ized by social disorganization, instability, isolation or
disconnectedness, are at increased risk of acquiring
many types of disease.[324-328] James Lynch provides a
sobering statistic on the effects of social isolation on
individuals. His research in social isolation shows that
loneliness produces a greater risk for heart disease
than smoking, obesity, lack of exercise and excessive
alcohol consumption combined.[329]
On the other hand, there is an abundance of literature
showing that close relationships and social networks
are highly protective. Numerous studies of diverse
populations, cultures, age groups and social strata
have shown that individuals who are involved in close
and meaningful relationships have significantly
reduced mortality, reduced susceptibility to infec-
tious and chronic disease, improved recovery from
post-myocardial infarction and improved outcomes
in pregnancy and childbirth.[330-332]
There are practical steps and practices that can be
taken to build and stabilize organizational coher-
ence and resilience. There are increasing numbers of
hospitals, corporations, military units, schools and
athletic teams, which are actively working towards
increasing their team, group or organizational coher-
ence. We have found that collective coherence is built
by rst working at the individual level. As individuals
become more capable of self-management, the group
increases its collective coherence and can achieve
its objectives more effectively.
This section contains a summary of a few examples
of organizations that have provided self-regulation
skills combined with heart-rhythm coherence training.
Overall, the results show improved workplace com-
munication, satisfaction, productivity, lower health-
care costs, innovative problem-solving and reduced
employee turnover, all of which can translate into a
signicant return on investment, not only nancially,
but also socially.
A number of hospitals that have implemented Heart-
Math training programs for their staff have seen in-
creased personal, team and organizational benets.
The measures most often assessed are staff retention
and employee satisfaction. For example, a study con-
ducted at the Mayo Clinic Hospital in Phoenix, Ariz.
evaluated the personal and organizational effects
of the HeartMath program on reducing stress and
improving the health of oncology nurses (n = 29), and
clinical managers (n = 15).[333]
The compelling imperative for the project was to nd a
positive and effective way to address the documented
high stress levels of health-care workers and explore
the impact of a positive coping approach on Per-
sonal and Organizational Quality Assessment-Revised
(POQA-R) scores at baseline and seven months after
the training program. Personal and organizational
indicators of stress decreased in the expected direc-
tions in both groups.
Figure 10.1 shows the results for the personal indica-
tors of stress scales on the POQA-R for the oncology
staff from pre-intervention to seven months post-
intervention. Statistically signicant differences were
found for each of the personal indicators (positive
outlook, gratitude, motivation, calmness, fatigue,
anxiety, depression, anger management, resentful-
ness and stress symptoms). Figure 10. 2 shows the
results for the organizational indicators of stress fac-
tors on the POQA-R for the oncology staff. Although
all of the indicators trended in the expected direction,
statistically signicant differences were found in the
indicators of goal clarity (p < 0.01), productivity (p <
0.001), communication effectiveness (p < 0.001) and
time pressure (p<0.001). Turnover on the oncology unit
was 13.12% pre-intervention and 9.8% seven months
post-intervention. In addition, incremental time on the
oncology unit dropped from 1.19 to 0.74 during the
same time interval, and employee satisfaction survey
scores for the unit increased in the following areas:
condence leadership was responding to issues/con-
cerns; condence the organization was taking genuine
interest in employees’ well-being and showing a desire
to continuously improve service on the unit; speaking
their minds without fear; respect between physicians
and allied health; and overall job satisfaction.
83
© Copyright 2015 HeartMath Institute
Figure 10.1 Oncology staff group, matched pairs analysis
of personal indicators of stress from the Personal and
Organizational Quality Assessment, at baseline and seven
months post-intervention.
Figure 10.2 Oncology staff group, matched pairs analysis of
organizational scales from the Personal and Organizational
Quality Assessment, at baseline and seven months post-
intervention.
Figure 10.3 depicts the results of the POQA-R on the
personal indicators of stress factors for the leader-
ship group from pre-intervention to seven months
post-intervention. Statistically signicant differences
were found in the personal indicators of gratitude (p<
0.001), fatigue (p< 0.01), depression (p < 0.05), anger
management (p<0.01), resentfulness (p<0.001) and
stress symptoms (p<0.01). Figure 10.4 depicts the
results of the organizational indicators of stress fac-
tors on the POQA-R for the leadership group. Statisti-
cally signicant differences between baseline and
seven months post-intervention were found on the
indicators of manager support (p < 0.05) and value
of contribution (p < 0.05).
Figure 10.3 Leadership group, matched pairs analysis
of personal indicators of stress from the Personal and
Organizational Quality Assessment, at baseline and seven
months post-intervention.
Figure 10.4 Leadership group, matched pairs analysis of
organizational scales from the Personal and Organizational
Quality Assessment, at baseline and seven months post-
intervention.
The authors state that the ndings from this study
demonstrate stress and its symptoms are problem-
atic issues for hospital and ambulatory clinic staff as
evidenced by baseline measures of distress. Further,
a workplace intervention was feasible and effective in
promoting positive strategies for coping and enhanc-
ing well-being, personally and organizationally.
In a study conducted at the Faireld Medical Center,
a 222-bed community hospital in Lancaster, Ohio, a
HeartMath workshop given in a series of six one-hour
sessions, with one two-hour follow-up session was
delivered to improve the well-being of hospital staff
and physicians.[334] Special thought and consideration
were given to being able to sustain the use of the self-
regulation techniques over the long-term. As a result,
Chapter 10: Social Coherence: Outcome Studies in Organizations
84
© Copyright 2015 HeartMath Institute
Science of the Heart
strategies were developed to integrate the program
into the hospital’s culture.
Four staff members from a variety of disciplines were
selected to be certied in the HeartMath program to
gain prociency in methodology, practices and tech-
niques. Two Workshops each week were offered from
August 2007 through December 2010. A total of 975
employees, or 48% of the staff, participated. Sustain-
ability of the program was aided by ensuring senior
leadership support, management team training, use
of techniques in committee and department meet-
ings, consulting, classes to local educators and open
workshops for employee family members.
Three metrics were selected to measure the success
of the program: employee satisfaction, absenteeism
rates and healthcare claims cost. Signicant cultural
and nancial return on investment was demonstrated.
Employees who received the HeartMath training expe-
rienced a 2:1 savings on health-care claims, compared
to employees who had not received training. Employee
opinion survey results demonstrated that employees
who had HeartMath training had higher overall satis-
faction scores than those who had not received train-
ing. HeartMath-trained participants demonstrated a
lower overall absenteeism rate, resulting in a $94,794
savings over three years.
It was concluded that the HeartMath program and
sustainability practices proved to be wise decisions
and continue to be valuable when initiating new
concepts in a stressful, changing environment. They
highlighted the fact that sustainability was the key to
long-term success and a true cultural change. Contin-
ued employee training of the HeartMath techniques
and continued use of the tools enriches the program
planning and implementation of new initiatives at
Faireld Medical Center.
In a study conducted by the National Health Service
(NHS) a publicly funded health service in the United
Kingdom that provides free point-of-use services
for UK residents, the HeartMath Revitalizing Care
Program was provided in workshops to four depart-
ments in an NHS trust from August to October 2011.[335]
Participants included staff from three clinical wards
and one reception area. Over a three-month period,
97 staff members participated in the workshops.
Evaluation of the project was conducted using the
Personal and Organizational Quality Assessment –
Revised 4 Scale (POQA-R4) as well as the pre- and
post-training measures of staff turnover, absence
rates and complaints.
The evaluation showed participants had demon-
strated improvements in nine of the 10 personal
qualities categories. These changes were statistically
signicant in eight areas, with fatigue and calmness
showing the greatest improvements. It should be
noted that the results of the pre- and post-comparison
of staff turnover, sickness absence and complaints
were inconclusive because of the short time frame
of the study.
A study was conducted at Chesapeake Regional
Medical Center (CRMC) in Virginia of 792 staff who
completed pre-and post-measures with Personal and
Organizational Quality Assessment (POQA) between
February 2009 and December of 2010.[336] The interven-
tion was a HeartMath workshop and training in Jean
Watson’s Theory of Caring (Caritas processes). As
a result of incorporating Caritas processes into the
HeartMath workshop, the program development team
at HeartMath created a workshop called “Revitalizing
Care,” which integrates the Caring Theory into the
HeartMath concepts and tools. There were signicant
improvements in positive outlook, gratitude, motiva-
tion, calmness, and anger management as well as
signicant reductions in fatigue, anxiety, depression,
resentfulness and physical symptoms of stress. The
organizational scales showed signicant improve-
ments in strategic understanding, condence in the
organization, feeling valued, freedom of expression,
communication, productivity and morale issues and
a decrease in intention to quit.
Caring science theory and practices have been part of
Kaiser Permanente’s strategic priority for the Kaiser
Permanente Northern Region since 2010. Its goal is
to ensure the continued spread across its medical
centers of practices guided by a caring sciences
framework that fosters caring-healing environments
and that reinforce helping-trusting relationships
85
© Copyright 2015 HeartMath Institute
between caregivers and patients. Kaiser staff were
selected to become certified HeartMath trainers.
There were four key elements in the trainer selection
process: 1) Trainers were selected in contextual align-
ment with Kaiser’s strategic goals. 2) Leader/RN staff
relationships were important. 3) Trainers had to be
committed to advancing cultures of caring science
and HeartMath. 4) The chief nursing ocers who
would become trainers had to emphasize consistent
leadership support. During a 12-month period from
June 2011 to June 2012, over 400 nurses, leaders
and other support staff were trained in the program.
Of those 400 participants, 263 completed both the
pre- and post-POQA surveys.[337] Eight of the 14 scales
showed statistically signicant changes in work atti-
tude, goal clarity, communication effectiveness, time
pressure, intention to quit, strategic understanding
and productivity. Improvements also were noted in
well-being, quality of life, impacts on patient satisfac-
tion, safety, and reduction of absenteeism. Addition-
ally, benets included improved relationships between
nursing staff and leaders. The trainers reported being
deeply affected on professional and personal levels.
________________________________
“HeartMath’s programs have enabled our
leaders to sustain peak performance, to manage
more efciently in a changing environment
and to maintain work/life balance. For our staff,
it has made the difference between required
courtesy and genuine care.
—Chief Operating Ocer Tom Wright,
Delnor Community Hospital
_________________________________
Other examples illustrating the effects of implement-
ing the HeartMath self-regulation program come
from the Cape Fear Valley Medical System in Cape
Fear, North Carolina, which reduced nurse turnover
from 24% to 13%; and Delnor Community Hospital in
Chicago, which experienced a similar reduction, 27%
to 14%, in addition to a dramatic improvement in em-
ployee satisfaction, results that have been sustained
over a 10-year period. Similarly, the Duke University
Health System reduced turnover in its emergency
services division from 38% to 5%.
An analysis of the combined psychometric data from
8,793 health-care workers with matched pre- and
post-POQA data collected before and six weeks af-
ter completion of a HeartMath self-regulation skills
training program produced many positive results.
Fatigue, anxiety, depression, anger and physical stress
symptoms declined greatly, while positive outlook,
gratitude, motivation and calmness improved signi-
cantly (Figure 10.5).
Figure 10.5 Shows matched pre- and post-data from the
POQA from 8,793 health-care workers collected before and
six weeks after completion of HeartMath training programs.
Studies In Law Enforcement
Organizations
Several studies with police officers have found
their capacity to recognize and self-regulate their
responses to stressors in both work and personal
contexts was signicantly improved after learning the
HeartMath self-regulation skills.
One study explored the nature and degree of physi-
ological activation typically experienced by ocers on
the job and the effects of HeartMath’s Resilience Ad-
vantage training program on a group of police ocers
from Santa Clara County, California.[53] Areas assessed
included vitality, emotional well-being, stress coping
and interpersonal skills, work performance, workplace
effectiveness and climate, family relationships, and
physiological recalibration following acute stressors.
Chapter 10: Social Coherence: Outcome Studies in Organizations
86
© Copyright 2015 HeartMath Institute
Science of the Heart
Physiological measurements were obtained to deter-
mine the real-time cardiovascular effects of acutely
stressful situations encountered in highly realistic
simulated police calls used in police training, and to
identify ocers at increased risk of future health chal-
lenges. The results showed that the resilience-building
training improved ocers’ capacity to recognize and
self-regulate their responses to stressors in both
work and personal contexts. Ocers experienced
signicant reductions in stress, negative emotions
and depression, compared to a control group, and in-
creases in peacefulness and vitality, compared to the
control group. (Figures 10.6 and 10.7). Improvements
in family relationships, more effective communication
and cooperation within work teams, and enhanced
work performance also were noted.
Heart-rate and blood-pressure measurements taken
during simulated police-call scenarios showed that
acutely stressful circumstances typically encountered
on the job resulted in a tremendous degree of physi-
ological activation, from which it took a considerable
amount of time to recover (Figure 10.8). Autonomic
nervous system assessments based on heart rate
variability analysis of 24-hour ECG recordings revealed
that 11% of the ocers were at higher risk, which was
more than twice the percentage typically found in the
general population.
Figure 10.6. Improvements in stress and emotional well-being.
Compares the differences between the average pre- and
post-training scores for each variable as measured by the
Personal and Organizational Quality Assessment. Compared
to the control group, participants trained in the Resilience
Advantage program exhibited signicant reductions in distress,
depression and global negative emotion, and increases in
peacefulness and vitality. The global negative emotion score
is the overall average of the individual scores for the anger,
distress, depression and sadness constructs. Note that the
control group experienced a marked rise in depression over
the same time period. †p < .1, *p < .05, **p < .01.
Figure 10.7 Changes in physical stress symptoms. Shows the
changes in ve physical symptoms of stress for all participants
at the start of the study and 16 weeks later (four weeks after
completion of the training).
87
© Copyright 2015 HeartMath Institute
Figure 10.8 This graph provides a typical example of the ability
of an ocer from the experimental group to shift and reset after
a domestic violence scenario. Note that when the scenario
ends, the ocer’s heart rate initially falls, but remains elevated
in a range above the normal baseline When this ocer used
the Freeze Frame Technique, there was an immediate, further
reduction in the heart rate back to baseline. In pre-training
scenarios it took on average, 1 hour and 5 minutes before
returning to baseline values.
Key Benets of the HeartMath Training for
Police Ocers*
• Increased awareness and self-management
of stress reactions.
Greater condence, balance and clarity under
acute stress.
• Quicker physiological and psychological
recalibration following acute stress.
Improved work performance.
• Reduced competition, improved communication
and greater cooperation within work teams.
• Reduced distress, anger, sadness and fatigue.
• Reduced sleeplessness and physical stress
symptoms.
• Increased peacefulness and vitality.
• Improved listening and relationships with family.
*Compiled from the results of psychological and performance assessments, and
a semi-structured interview conducted post-training.
A study was conducted with 10 male and four female
police ocers and two dispatchers with the San Diego
Police Department. It included self-regulation skills
training comprising an introductory two-hour training
session, and telephone mentoring sessions spread
over a four-week period by experienced HeartMath
mentors. In addition, the officers were issued an
iPad app called Stress Resilience Training System
(SRTS), which includes training modules on stress
and its effects, HRV coherence biofeedback, a series
of HeartMath self-regulation techniques and HRV-
controlled games.
Outcome measures were the Personal and Orga-
nizational Quality Assessment (POQA) survey, the
mentors’ reports of their observations and records of
participants’ comments from the mentoring sessions.
The POQA results were overwhelmingly positive: All
four main scales showed improvement, including emo-
tional vitality, up 25% (p=0.05), and physical stress, up
24% (p=0.01). Eight of the nine subscales showed
improvement, with the stress subscale improving ap-
proximately 40% (p=0.06). Participant responses also
were uniformly positive and enthusiastic. Individual
participants praised the program and related improve-
ments in both on-the-job performance and personal
and familial situations.[193]
Fighter Pilot Study
A study of 41 ghter pilots engaging in ight simulator
tasks to better understand pilots’ workload and visual
attention in the cockpit while conducting a simulated
air-to-air tactic operations found a signicant cor-
relation between higher levels of performance and
heart-rhythm coherence as well as lower levels of
frustration. The study also found that the objective
measurement of workload and attention distribu-
tion, as reected in HRV coherence and eye-tracking,
provided more reliable indicators than self-report ap-
proaches and that HRV coherence scores of expert
pilots and novice pilots were signicantly different.[191]
HeartMath in a Prison Environment
A study conducted by Lori Bosteder and Sara Hargrave
in the Coffee Creek Women’s Correctional Facility, in
Wilsonville, Ore. sought to determine whether emo-
tional intelligence training would help female inmates
Chapter 10: Social Coherence: Outcome Studies in Organizations
88
© Copyright 2015 HeartMath Institute
Science of the Heart
better manage the emotional diculties of living and
learning within a prison environment.[338] Many of the
women who enter prison have diculty in emotion
self-management and positive social engagement.
They often come from dysfunctional or abusive back-
grounds, and many have become accustomed to abus-
ing drugs and/or alcohol as a means of coping with
distressing emotions. The highly charged emotional
environment of a women’s prison is augmented by the
inherent struggles of prison life, including the loss of
most freedoms and nearly all privacy. This emotional
chaos frequently impairs inmates’ ability to learn and
acquire new skills in prison work-based education pro-
grams, and may also deter their successful transition
back into society.
The study participants were 17 women in minimum
security. These women were all students of the
prison’s 18-month work-based education program
in computer technology. Over a 10-week period, the
women participated in three workshops that focused
on basic emotional intelligence concepts and skills in
the areas of self-awareness, self-management, social
awareness and relationship management. HeartMath
material, practice of its tools and heart-rhythm coher-
ence feedback were the major focus of the training.
Participants read and completed self-reective exer-
cises in HeartMath’s Transforming Stress, Transforming
Anxiety and Transforming Anger books. Practice of the
Neutral and Heart Lock-In self-regulation techniques
was integrated into the daily classes, as was heart-
rhythm coherence feedback training with handheld
emWave devices. Each woman also received individu-
alized coaching and training in HeartMath emotion-
management tools and use of the heart-rhythm feed-
back technology. The outcome measures used in the
study were the Emotional Intelligence Appraisal-ME,
the Brief Symptom Inventory (BSI) self-report survey,
discipline reports for the participants that were re-
corded by correctional ocers four months before the
training and four months after. In addition, observation
notes over the 10-week study period were recorded by
the computer technology class instructor, who noted
student comments and any changes in their behav-
iors and interactions as they practiced the emotional
awareness and self-management skills. Also, each
participant’s extensive evaluation at the end of the
study provided both quantitative and qualitative data
on her experiences in the program.
Analysis of the pre- and post-data showed signicant
reductions in symptoms of emotional distress, obses-
sive-compulsive patterns, depression and anxiety on
the BSI, and signicant increases in self-awareness,
self-management, social awareness and relationship
management on the Emotional Intelligence Appraisal
scales. The discipline reports showed a signicant de-
crease in discipline problems outside the classroom.
Qualitative data also supported the program’s effec-
tiveness. Most participants reported in their evalu-
ations signicant benets to themselves and their
social relationships. A few reported an initial increase
in depression and anxiety as a result of feeling for the
rst time in years, but they improved with support
from the instructor. The computer technology course
instructor observed major improvement in the learn-
ing environment and growth in her students’ ability to
self-regulate and get along with others. Two students
who were paroled after the study contacted the train-
ers and reported that they were using the HeartMath
skills to manage the struggles they were facing on the
outside and that they were creating better outcomes
for themselves than they would have in the past.
The researchers observed that crucial factors in the
program’s success were a supportive group and the
consistent support and encouragement provided by
the course instructor as students experienced the
initial disorientation created by the psychological
changes resulting from their emotion-management
practice. Because the group met daily during the week,
a classroom setting worked well to provide this close
attention and support. The program led to important
psychosocial improvements in the participants over
a relatively brief period of time and appeared to sig-
nicantly enhance inmates’ capacity to learn within
the prison setting and to eventually successfully
reintegrate into society.
89
© Copyright 2015 HeartMath Institute
Global Coherence Research:
Human-Earth Interconnectivity
Every cell in our body is bathed in an external and internal environment of uctuating invisible magnetic forces
that can affect virtually every cell and circuit in biological systems. Therefore, it should not be surprising that
numerous physiological rhythms in humans and global collective behaviors are not only synchronized with solar
and geomagnetic activity, but disruptions in these elds can create adverse effects on human health and behavior.
Chapter 11: Global Coherence Research: Human-Earth Interconnectivity
The most likely mechanism for explaining how solar
and geomagnetic inuences affect human health and
behavior are a coupling between the human nervous
system and resonating geomagnetic frequencies,
Schumann resonances, which occur in the earth-
ionosphere resonant cavity, Alfven waves and other
very low-frequency resonances. It is well established
that these resonant frequencies directly overlap with
those of the human brain, cardiovascular and auto-
nomic nervous systems.
In order to conduct research on the potential interac-
tions between human health and behavior, a global
network of 12 ultrasensitive magnetic eld detectors,
specically designed to measure the earth’s mag-
netic resonances, are being installed strategically
around the planet. An important goal of the project
is to motivate as many people as possible to work
together in a more coherent and collaborative manor
to elevate collective human consciousness. If we are
persuaded that not only external elds of solar and
cosmic origins, but also human consciousness and
emotion can affect the mental and emotional states
of others’ consciousness, it broadens our view of
what interconnectedness means and how it can be
intentionally utilized to shape the future of the world
we live in. It implies that our attitudes, emotions and
intentions matter and that coherent, cooperative in-
tent can have an important inuence on global events
and the quality of life on Earth.
THE GLOBAL COHERENCE INITIATIVE
The Global Coherence Initiative (GCI) was launched
by HeartMath Institute in 2008. It is a science-based,
co-creative initiative that has the goal to unite millions
of people globally in heart-focused care and intention.
GCI employs several strategies to help increase
personal, social and global coherence. An internet-
based network connects people globally who want to
participate in creating a shift in global consciousness.
In 2015, over 160,000 people in 154 countries were
involved in the initiative. Members of GCI, known as
GCI ambassadors, receive regular updates informing
them where to direct their energetic contributions
of heart-focused care and intention. GCI also helps
to educate the global community by providing tools
and technologies for increasing individual, social and
global coherence.
The following GCI hypotheses guide the
ongoing collaborative research:
1. Human and animal health, cognitive func-
tions, emotions and behavior are affected
by planetary magnetic and energetic elds.
2. The earth’s magnetic elds are carriers of bio-
logically relevant information that connects
all living systems.
3. Each individual affects the global information
eld.
4. Large numbers of people creating heart-cen-
tered states of care, love and compassion will
generate a more coherent eld environment
that can benet others and help offset the cur-
rent planetarywide discord and incoherence.
CHAPTER 11
90
© Copyright 2015 HeartMath Institute
Science of the Heart
Embedded within the above hypotheses is a related
hypothesis that human emotions and conscious-
ness interact with and encode information in the
geomagnetic eld. Thereby, information is communi-
cated nonlocally between people at a subconscious
level, which, in effect, links all living systems and
inuences collective consciousness. Thus, a feed-
back loop exists between all human beings and the
earth’s energetic systems. It is further proposed that
when coherently aligned individuals are intentionally
creating physiologically coherent waves, they more
effectively resonate with and encode information in
the planetary magnetic elds. These magnetic elds
act as carrier waves, thereby positively inuencing all
living systems contained within the eld environment
and the collective consciousness.[339]
Figure 11.1. Existing and proposed locations for the global network of monitoring sites as of fall 2015. These sites are specically
designed to measure the magnetic resonances in the earth/ionosphere cavity, resonances that are generated by the vibrations
of Earth’s geomagnetic eld lines, and ultra-low frequencies that occur in the earth’s magnetic eld.
Global Coherence Monitoring System
The Global Coherence Monitoring System (GCMS)
gathers scientic data on Earth’s electromagnetic
elds, with state-of-the-art magnetometers located on
suitable sites around the world. GCI uses the GCMS to
measure and explore uctuations and resonances in
the earth’s magnetic elds and in the earth-ionosphere
resonant cavity in order to conduct research on the
mechanisms of how the earth’s elds affect human
mental and emotional processes, health and collective
behavior. In addition, we hope to investigate whether
changes in the earth’s magnetic elds occur before
natural catastrophes such as earthquakes, volcanic
eruptions and human events such as social unrest
and terrorist attacks.
This system is the rst global network of GPS time-stamped detectors designed to continuously measure
magnetic signals that occur in the same range as human physiological frequencies such as the brain and car-
diovascular systems. A total of 12 magnetometers are planned to complete the global network. Each GCMS site
includes ultrasensitive magnetic eld detectors specically designed to measure the magnetic resonances in
the earth/ionosphere cavity, resonances that are generated by the vibrations of the earth’s geomagnetic eld
lines and ultra-low frequencies that occur in the earth’s magnetic elds, all of which have been shown to affect
human health, mental and emotional processes and behaviors.
91
© Copyright 2015 HeartMath Institute
Each monitoring site detects the local alternating
magnetic eld strengths over a relatively wide fre-
quency range (0.01-300 hertz) while maintaining a
at-frequency response. There are several networks
of ground-based uxgate magnetometers around the
world, along with several space weather satellites,
which measure the strength of the earth’s magnetic
elds and geomagnetic disturbances (Kp).
The GCI monitoring system helps us better understand
how people and animals are affected by the rhythms
and resonant frequencies in Earth’s magnetic eld
as well as enabling us and other researchers to bet-
ter understand the interconnections between solar
and other external forces on the planetary magnetic
eld environment. Figure 11.2 shows a photo of the
monitoring site located in Boulder Creek, California.
At the time of this writing, six sites were operational.
They are located at the HeartMath Research Center
in Northern California, the eastern province of Saudi
Arabia, Lithuania, Canada, North Island of New Zea-
land, and the east coast of South Africa.
Figure 11.2. The monitoring site at the HeartMath Research
Center, located in Boulder Creek, California.
The data acquisition infrastructure captures, stamps
with time and global positioning data, and transmits
the data to a common server. In addition, each site
has a random number generator (RNG) that is part of
the Global Consciousness Project (GCP) network. The
monitoring system tracks changes in geomagnetic
activity due to solar storms, changes in solar wind
speed, disruption of Schumann resonances (SR) and,
potentially, the signatures of major global events
that have a strong emotional component. A growing
body of data also suggests that changes occur in
ionospheric activity before earthquake activity.[340, 341]
We make our data freely available to other research
groups who may wish to explore how it may be utilized
to predict earthquakes and other events. Thus, the net-
work will provide a signicant research tool to further
understand how solar and geomagnetic disturbances
and rhythms affect human health, emotions, behaviors
and consciousness and vice versa.
Earth’s Energetic Systems and Human
Health and Behavior
Every cell in our bodies is bathed in an external and
internal environment of uctuating invisible magnetic
forces.[205] Because uctuations in magnetic elds can
affect virtually every circuit in biological systems, [5, 205,
342] human physiological rhythms and global behaviors
are not only synchronized with solar and geomagnetic
activity, but disruptions in these elds can create
adverse effects on human health and behavior.[343-345]
Research by Burch et al.[346] and Rapoport et al.[347]
provide evidence that melatonin levels are reduced
during increased solar and geomagnetic activity.
Cancer, neurological diseases, acute heart disease and
heart attacks among other diseases and accelerated
aging are all related to melatonin levels that are too
low. In addition, clinical measurements have identi-
ed signicant changes in blood pressure, blood ow,
aggregation and coagulation, cardiac arrhythmia and
heart rate variability during increased geomagnetic
activity events, all of which are inuenced by mela-
tonin levels.[232, 343]
EEG patterns, heart rate, blood pressure and reaction
times were measured in a group of people by Doronin
et al.[343]
The authors noted that the oscillations in
the magnetic eld data had identical periods in the
monitored EEG alpha rhythm. This conrms that
whole-body changes occur in conjunction with geo-
magnetic activity which are reflected in changing
heart and brain rhythms.
Another study by Pobachenko et al,[348] monitored
the Schumann resonances (SR) and the EEG in a
frequency range of 6 to 16 hertz simultaneously. Dur-
ing a daily cycle, individuals studied showed varia-
tions in the EEG similar to changes in the SR. Hence,
the biological EEG rhythm is characteristic of the
daily rhythm of the SR.[348] The lowest frequency SR
is approximately 7.83 hertz, with a daily variation of
Chapter 11: Global Coherence Research: Human-Earth Interconnectivity
92
© Copyright 2015 HeartMath Institute
Science of the Heart
about ± 0.5 hertz. The other frequencies are ~ 14,
20, 26, 33, 39 and 45 hertz. Figure 11.3 shows the
frequencies of the SR, which are closely overlapping
with alpha (8 to 12 hertz), beta (12 to 30 hertz) and
gamma (30 to 100 hertz) brain waves.
Figure 11.3. Schuman resonance data recorded from the GCI
sensor site in Boulder Creek, Calif.
Because the brain is a very sensitive electromagnetic
organ, changes in geomagnetic activity and SR inten-
sities appear to alter brain-wave and neurohormone
responses. Geomagnetic storms are also related to
human health effects and death.[349, 350] Altered EEG
rhythms have been observed by Belov et al.[351] While
low-frequency magnetic oscillations (around 3 hertz)
had a sedative effect in the Pobachenko et al. study,
stronger oscillations of around 10 hertz stresses and
stimulates people.[351]
Increased solar activity can disturb the biological
rhythm of humans and exacerbate existing dis-
eases. However, deviations are observed for some
individuals, which can be caused by the individual’s
adaptive ability.
Increased solar activity and geo-
magnetic activity also is correlated to
a signicant
increase in heart attacks and incidence of death,
myocardial infarction incidence, [352] a 30% to 80%
increase in hospital admissions for cardiovascular
disease, cardiovascular death, depression, mental
disorders, psychiatric admission, suicides, homicides
and trac accidents.[344, 353-357]
Birthrates were observed in the Pobachenko et al.
study to drop and mortality rates to increase during
increased solar and geomagnetic activity (GMA), and
migraine attacks could be triggered.[358]
Persinger and Halberg have independently shown
that war and crimes were correlated to GMA.[359] Ad-
ditionally, research has indicated that an increase in
magnetic Pc frequencies (continuous pulsations), can
affect the human cardiovascular system because Pc-1
frequencies are in a comparable range with those of
the human cardiovascular system and rhythms.[360]
A study carried out in India on animals and humans
also demonstrated that humans and animals can
be affected by Pc frequencies.[361] The experiments
showed changes in the electrophysiological, neuro-
chemical and biochemical parameters. The subjects
experienced uneasiness, confusion, restlessness and
a lack of a sense of well-being when subjected to the
pulsating elds. Some also complained of headaches.
[361] It is important to note that of all the bodily systems
studied, rhythms of the heart and brain thus far appear
to be most strongly affected by changes in geomag-
netic conditions.[205, 348, 349, 357, 362-367]
Historically, many cultures believed their collective
behavior could be inuenced by the sun and other ex-
ternal cycles and inuences. This belief has proven to
be true. On a larger societal scale, increased violence,
crime rate, social unrest, revolutions and frequency
of terrorist attacks have been linked to the solar
cycle and the resulting disturbances in the geomag-
netic eld.[345, 359, 368-371] The rst scientic evidence of
this belief was provided by Alexander Tchijevsky, a
Russian scientist who noticed that more severe bat-
tles during World War I occurred during peak sunspot
periods.[371] He conducted a thorough study of global
human history dating back to 1749 and compared
the period to the solar cycles through the period, up
to 1926. Figure 11.4, reconstructed from Tchijevsky’s
original data, plots the number of signicant human
historical events compared to the solar cycle from
1749 to 1926.[371]
93
© Copyright 2015 HeartMath Institute
0
5
10
15
1840 1860 1880 1900 1920
0
50
100
150
1840 1860 1880 1900 1920
# of Sunspots # of Important
Historical Events
0
5
10
15
1840 1860 1880 1900 1920
0
50
100
150
1840 1860 1880 1900 1920
0
5
10
15
1840 1860 1880 1900 1920
0
50
100
150
1840 1860 1880 1900 1920
0
5
10
15
1840 1860 1880 1900 1920
0
50
100
150
1840 1860 1880 1900 1920
# of Sunspots # of Important
Historical Events
0
5
10
15
1750 1770 1790 1810 1830
0
50
100
150
1750 1770 1790 1810 1830
# of Sunspots # of Important
Historical Events
0
5
10
15
1750 1770 1790 1810 1830
0
50
100
150
1750 1770 1790 1810 1830
0
5
10
15
1750 1770 1790 1810 1830
0
50
100
150
1750 1770 1790 1810 1830
# of Sunspots # of Important
Historical Events
Year
Figure 11.4. Tchijevsky’s original data. The blue line plots the yearly number of important political and social events such as the
start of a war, social revolutions, etc. The red line plots solar activity, as indicated by the number of sunspots from 1749 to 1922.
The histories of 72 countries were compiled, and it was found that 80% of the most signicant events occurred during the solar
maximum, which correlates with highest periods of geomagnetic activity.
Energetic Inuxes and Human
Flourishing
Solar activity, in addition to being associated with social
unrest, also has been related to the periods of greatest
human ourishing with pronounced spurts in architec-
ture, arts, science and positive social change.[372] We
can learn from past mistakes and consciously choose
new ways of navigating energy inuxes to create peri-
ods of human ourishing and humanitarian advances.
When outdated structures that do not serve humanity
collapse, an opportunity opens for them to be replaced
with more suitable and sustainable models. Such posi-
tive change can affect the political, economic, medical
and educational systems, as well as relationships of
individuals at work and home and in communities.
At times of such heightened energy inux, we have
the greatest opportunity to create positive change
in our world. We can learn from past mistakes and
consciously choose new ways of navigating energy
inuxes to create periods of human ourishing and
advances.
It is well established that the earth and ionosphere
generate a symphony of resonant frequencies that
directly overlap with those of the human brain and
cardiovascular system. The central hypothesis is that
changes in these resonances can in turn inuence the
function of the human autonomic nervous system
brain, and cardiovascular system.
Interconnectedness Study
Data and results from the Interconnectedness Study
were presented in McCraty et al., 2012.[339] In 2010,
1,643 Global Coherence Initiative members from 51
Chapter 11: Global Coherence Research: Human-Earth Interconnectivity
94
© Copyright 2015 HeartMath Institute
Science of the Heart
countries completed a twice-weekly survey at random
times six days each week over a six-month period. The
survey contained six valid scales: positive affect, well-
being, anxiety, confusion, fatigue and physical symp-
toms. The survey data were subjected to correlation
analysis with a number of planetary and solar activity
variables such as solar wind speed, magnetic eld and
plasma data, measures of energetic protons, solar ux
and geomagnetic activity indices. When solar wind
speed, Kp, Ap (Kp and Ap magnetic indices were de-
signed to describe variations in the geomagnetic eld)
and polar cap activity increased, positive affect among
the participants decreased. Well-being scores were
negatively correlated with solar wind speed, Kp-index,
Ap-index and polar cap magnetic activity. Thus, when
solar wind speed increased and the geomagnetic eld
was disturbed, the levels of fatigue, anxiety and mental
confusion increased. The study also resulted in some
unexpected ndings. For example, the solar radio ux
index was positively correlated with reduced fatigue
and improved positive affect, indicating there are
mechanisms that improve human well-being that are
not yet fully understood. Clearly, additional research
needs to be conducted in order to understand the ef-
fects of the various variables and the time sequence
of their effects.[339]
Examples of Magnetometer Data
Data collected by our magnetometers in different lo-
cations is providing some new insights into globally
correlated activity and signicant local differences.
Figure 11.5. Simultaneously recorded data from Boulder Creek,
Calif. and Alberta, Canada, sites.
Figure 11.5 shows an example of Pc 1 activity detect-
ed at the California and Canada sites. While the Pc 1
data in Canada displays a greater amplitude, and while
most of the rhythm is synchronized, there are periods
in which it is ~180 degrees out of phase. Further data
processing is currently under way to examine other
parameters in greater depth, such as longitudinal and
latitudinal parameters, time of the day and other solar
and geomagnetic parameters and their implications
on human health indicators.
HRV Studies
Among physical environmental variables affecting bio-
logical processes and human health, the natural varia-
tion in the geomagnetic eld in and around the earth
reportedly has been involved in relation to several
human cardiovascular variables. These include blood
pressure,[373] heart rate (HR) and heart rate variability
(HRV).[375, 376] Although there is mounting evidence for
such effects, they are far from being fully understood.
Several studies have found signicant associations
between geomagnetic storms and decreased heart
rate variability (HRV), indicating a possible mecha-
nism linking geomagnetic activity with increased inci-
dents of coronary disease and myocardial infarction.
[350, 352, 355] One study that analyzed weeklong recordings
found a 25% reduction in the VLF rhythm during mag-
netically disturbed days, compared to quiet days. The
LF rhythm also was reduced signicantly, but the HF
rhythms were not.[376]
In order to further investigate the potential correla-
tions between solar and magnetic factors and HRV,
we undertook a collaborative study with Dr. Abdullah
A. Al Abdulgader, director of Prince Sultan Cardiac
Center in Al Ahsa, Saudi Arabia, spanning a ve-month
period. A total of 960 24-hour HRV recordings were
obtained from a group of 16 women aged 24 to 31
(mean age 31). HRV data was collected for 24 hours
a day, three consecutive days each week over ve
months with HRV recorders between March and Au-
gust of 2012. The HRV measures assessed were the
interbeat-interval (IBI), SDNN, RMSSD, total power,
very-low-frequency (VLF), low-frequency (LF) and
high-frequency (HF) power, and the LF/HF ratio. The
95
© Copyright 2015 HeartMath Institute
solar activity and magnetic variables were: solar wind
speed, Kp and Ap index, PC(N), sunspot number, solar
radio ux (f10.7), cosmic rays, Schumann resonance
integral (area under the curve around 7.8 hertz) and
the mean and standard deviation (SD) of the time-
varying magnetic eld data collected at GCI sites in
Boulder Creek, Calif. (GCI 1) and Al Ahsa, Saudi Arabia
(GCI 2). The mean and standard deviation were com-
puted hourly. The mean eld variation reects ultra-
low frequency changes and SD, which is highly cor-
related with total spectral power and reects overall
variance in the eld. Circadian effects were removed
from both environmental and HRV variables. For each
of the 16 study participants, a correlation matrix was
calculated between each environmental and HRV
variable. Overall, the study conrms that autonomic
nervous system activity as reected by HRV measures
is affected by solar and geomagnetic inuences. All
of the HRV measures, with the exception of IBIs, were
negatively correlated with solar wind speed, and LF
and HF power were negatively correlated with the
magnetic eld mean data collected from the Saudi
Arabia site, but not the California site, suggesting that
local measurements are important. Surprisingly, there
were a number of positive correlations. The f10.7 index
was correlated with increased HRV in all measures
with the exception of the SD of the HRV and IBIs. The
SD of the magnetic eld variation from both the Saudi
Arabia and California sites was positively correlated
with RMSSD and HF power, both of which reect
parasympathetic activity, and Schumann resonance
power was positively correlated with the IBIs.
Although there were a number of global correlations,
at the individual level, the HRV responses varied and
in some cases different individuals showed different
responses to the same environmental variable.
When looking at the data from both the Interconnect-
edness Study and the HRV data, it is clear that when
the earth’s magnetic eld was calmer or the solar
radio ux was increased, the study participants felt
better, were more mentally and emotionally stable
and had higher levels of HRV. Conversely, when the
magnetic eld was disturbed, HRV was lower and
participants’ emotional well-being and mental clarity
were adversely affected.
Figure 11.6 shows an example of healthy participants
HRV-HF power plotted along with the total magnetic
power spectrum from the magnetometer site in Cali-
fornia over a 30-day period. This data is from a study
of 10 participants located in northern California whose
HRV was continuously monitored over a 30-day period.
The magnetic eld data in the plot, which is inversely
correlated, has been inverted in the plot to help il-
lustrate the visual correlation, which can be clearly
seen in the graph.
Figure 11.6. Example of one participant’s high-frequency
power derived from the individual’s HRV and the total power
of the time varying magnetic eld at the California site over
a 30-day period.
Interconnectivity of All Living Systems
through the Earth’s Magnetic Field
Magnetic Fields Carry Biologically Relevant
Information
The evidence that human health and behavior are glob-
ally inuenced by solar and geomagnetic activity is
relatively strong and convincing. We also have shown
in our laboratory that the electromagnetic eld of an
individual’s heart can be detected by nearby animals or
the nervous systems of other people.[378] (Also, see the
Energetic Communication chapter in this document).
GCI hypothesizes that the earth’s magnetic elds
are carriers of biologically relevant information that
connect all living systems. Thus, we each affect the
global information eld.
Chapter 11: Global Coherence Research: Human-Earth Interconnectivity
96
© Copyright 2015 HeartMath Institute
Science of the Heart
There is experimental evidence that human bio-
emotional energy can have a subtle, but signicant
(scientically measurable) nonlocal effect on people,
events and organic matter.[339] It is becoming clear that
a bioelectromagnetic eld such as the ones radiated
by the human heart and brain of one person can af-
fect other individuals and the “global information eld
environment.” For example, research conducted in our
laboratory has conrmed the hypothesis that when an
individual is in a state of heart coherence, the heart
radiates a more coherent electromagnetic signal into
the environment and that individual is more sensitive
to detecting the information in the elds radiated by
others.[378]
Of all the organs, the heart generates the largest rhyth-
mic electromagnetic eld, one that is approximately
100 times stronger than the one the brain produces.
This eld can be detected several feet from the body
with sensitive magnetometers. This magnetic eld
provides a plausible mechanism for how we can “feel”
or sense another person’s presence and emotional
state independent of body language or other factors.
We also have found there is a direct relationship
between the heart-rhythm patterns and the spectral
information encoded in the frequency spectra of the
magnetic eld radiated by the heart. Thus, informa-
tion about a person’s emotional state is encoded in
the intervals between the heartbeats, which is com-
municated throughout the body and into the external
environment.[378]
In a study on interpersonal effects of nonverbal
compassionate communication, measuring psycho-
physiological effects, Kemper and Shaltout found
signicant changes in the receiver’s autonomic ner-
vous system.[379] A growing body of evidence suggests
that an energetic eld is formed among individuals
in groups through which communication among all
the group members occurs simultaneously. In other
words, there is an actual “group eld” that connects
all the members.[59]
Morris [221] studied heart coherence in a group setting:
He investigated how people trained in maintaining
states of heart coherence for several minutes might
inuence participants untrained in heart coherence.
The results showed that the coherence of untrained
participants was indeed promoted by participants in
a coherent state.
Further support for the hypothesis that magnetic elds
are carriers of biologically relevant information comes
from a study conducted by Montagnier et al.[380] Mon-
tagnier discovered that epigenetic information related
to DNA could be detected as electromagnetic signals
in a highly diluted solution and that this information
could be transferred to and imprinted in pure water
that had never been exposed to DNA. Furthermore,
this information can instruct the re-creation of DNA
when the appropriate basic constituents of DNA are
present and extremely low electromagnetic frequency
elds of 7.8 hertz are present. They also showed that
the presence of the magnetic eld was needed for
the information transfer to occur.The authors also
state, a very low electromagnetic frequency eld that
transfers DNA information could come from natural
sources such as the Schuman resonances (SR), which
start at 7.83 hertz.
Michael Persinger, a well-known neuroscientist, also
has conducted numerous studies examining the ef-
fects of magnetic elds with the same magnitude
as the geomagnetic field on brain functions and
information transfer.[349, 364] Not only has he shown
that applying external elds similar to the SRs can
induce altered states of consciousness, but he also
has suggested in a detailed theory that the space
occupied by the geomagnetic eld can store informa-
tion related to brain activity and that this information
can be accessed by the human brain.[381] Persinger
also suggests that the earth’s magnetic eld can act
as a carrier of information between individuals and
this information, rather than the signal intensity, is
important for interaction with neural networks.[382] The
above ndings clearly support part of our hypothesis:
The earth’s magnetic elds are carriers of biologically
relevant information. We are further suggesting that
because humans have brain and heart frequencies
overlapping the earth’s magnetic eld , not only are
we receivers of biologically relevant information, but
these frequencies also can couple information to the
97
© Copyright 2015 HeartMath Institute
earth’s magnetic elds and thus feed information into
the global eld environment.
Interconnection between the Human Energy Field,
Collective Human Emotions and the Planetary
Energy Field
Our fourth hypothesis states: Large numbers of people
creating heart-centered states of care, love, and compas-
sion will generate a more coherent eld environment that
can benet others and help offset the current planetary-
wide discord and incoherence.
There also is a substantial body of evidence indicating
interactions between human emotions and a global
eld when large numbers of people have similar emo-
tional responses to events or organized global peace
meditations.[383-385] For example, quantum physicist
John Hagelin, has conducted research on the power
of the collective and concluded: “Since meditation
provides an effective, scientically proven way to
dissolve individual stress and if society is composed
of individuals, then it seems like common sense to
use meditation to similarly diffuse societal stress.[384]
A study conducted in 1993 in Washington, DC, showed
a 25% drop in the crime rate when 2,500 meditators
mediated over specific periods of time,[385] which
means that a relatively small group of a few thou-
sand were able to inuence a much larger group. The
question was then posed that if crime rates could be
decreased, could a group of meditators also inuence
social conicts and wars? A similar experiment was
done during the peak of the Israel-Lebanon war in the
1980s. Drs. Charles Alexander and John Davies at
Harvard University organized groups of experienced
meditators in Jerusalem, Yugoslavia and the United
States to meditate and focus attention on the area at
various intervals over a 27-month period. After con-
trolling statistically for weather changes, Lebanese,
Muslim, Christian and Jewish holidays, police activity,
uctuation in group sizes and other variant inuences
during the course of the study, researchers calculated
the levels of violence in Lebanon decreased 40% to
80% each time a meditating group was in place, with
the largest reductions occurring when the number
of meditators was largest. During these periods, the
average number of people killed during the war per
day dropped from 12 to three, a decrease of more
than 70%. War-related injuries declined by 68%.
Intensity level of conflict, another of the study’s mea-
sures, decreased by 48%.[383, 386]
Interconnection between Collective Human
Emotions, Random Number Generators and
the Geomagnetic Field
Former Princeton University Professor Roger Nelson,
chief scientist of the Global Consciousness Project
(GCP), provided further evidence of an interconnec-
tion between collective human emotionality and
global events. GCP maintains a worldwide network
of random number generators, (RNG) which produced
results that suggest that human emotionality affects
the randomness of these electronic devices in a glob-
ally correlated manner. Nelson said of the project: The
GCP is a long-term experiment that asks fundamental
questions about human consciousness. It provides
evidence for effects of synchronized collective atten-
tion – operationally dened global consciousness – on
a world-spanning network of physical devices. There are
multiple indicators of anomalous data structure, which
are correlated specically with moments of importance
to humans. The ndings suggest that some aspect of
consciousness may directly create effects in the mate-
rial world. This is a provocative notion, but it is the most
viable of several alternative explanations.[223]
Nelson also found clear evidence that larger events,
dened by the number of people engaged and their
level of “importance,” produces larger effects on the
global network. An interesting nding is a signicant
correlation between global events that elicit a high
level of emotionality from a large part of the world’s
population and periods of nonrandom order generated
by the RNGs.[387] For example, multiple independent
analyses of the network during the terrorist attacks
that took place in the United States on the morning
of Sept. 11, 2001 correlate with a large and signicant
shift in the output of the global network of RNGs.[388]
Although the mechanisms for how human emotions
create more coherence in the randomness of this
Chapter 11: Global Coherence Research: Human-Earth Interconnectivity
98
© Copyright 2015 HeartMath Institute
Science of the Heart
global network are not yet understood, the data clearly
show that they do have such affects. Moreover, the
data shows the odds-against-chance ratio is more
than 1 billion to 1.[388]
When an event is characterized by deep and wide-
spread compassion, the GCP effects are stronger, [223]
which could be explained by the fact that compassion
is related to interconnection and positive emotional
engagement. When we experience true feelings of
compassion, we tend to shift into a more coherent
physiological state [5] and are thus radiating more
coherent magnetic waves into the environment.[378]
Compassion is an emotional state that brings people
together and makes them coherent. We invest a small
part of our individual being to connect with others
and, as the GCP data indicate, with the global eld
environment. A study examining GCP data between
1998 and 2008 matched satellite-based interplanetary
magnetic eld (IMF) polarity with GCP-dened world
events such as meditations, celebrations, natural ca-
tastrophes or violence. Study results suggested that
RNG deviations may depend on a positive IMF polar-
ity coinciding with emotionally signicant conditions
and/or entropy changes.[389]
The CGP has investigated a number of theoretical
models that could potentially explain the global effect
they are detecting with the network.
In summary, here is an excerpt of GCP’s analysis:
Finally, a nonlinear dynamic eld model proposes that
individual minds are mutually interactive, and that
the interactions are responsible for an emergent eld
which depends on individual consciousness but is not
reducible to it. The model implies that the dynamic and
interactive qualities of consciousness also involve subtle
interactions with the physical world and that these are
responsible for certain anomalous phenomena such as
are found in the GCP experiment.[223]
We do not have magnetic data over a long enough
period of time to investigate how multiple collective
events associated with an outpouring of compassion
or other positive collective feelings potentially may
affect information that could be contained in the
geomagnetic eld. One of our goals, however, is to
test the hypothesis that large numbers of people in a
heart-coherent state and holding a shared intention can
encode physiologically patterned and relevant informa-
tion that is carried by the earth’s energetic and geomag-
netic elds. If living systems are indeed interconnected
and communicate with each other via such biological
and electromagnetic elds, it stands to reason that hu-
mans can work together in a co-creative relationship to
consciously increase the coherence in the global eld
environment. Likewise, it also makes sense that the
eld environment distributes the information it may
contain to all living systems within the eld.
Of course, the idea that shared intentions of people
in one location can inuence others at a distance is
not new. Such ideas have been the subject of numer-
ous studies that have looked at the effects of prayer,
meditation and groups sending intentions in various
experimental contexts.[390-392]
How can we have such an inuence on each other
at a distance? There are no clear answers yet, but
we hypothesize there is a unied eld that interacts
with and affects consciousness. We also suggest
that individually generated coherent waves are more
likely to be coupled to the larger collective eld envi-
ronment than waves from states of incoherence. The
GCI theory of change is that as a sucient number
of individuals increase their personal coherence, it
can lead to increased social coherence (families,
teams, organizations), and as increasing numbers
of social units (families, schools, communities, etc.)
become more coherently aligned, it in turn can lead
to increased global coherence, all of which is enabled
and advanced through self-reinforcing feedback loops
between humanity and the global eld environment.
This implies that every individual contributes to the
global eld environment and each person’s attitudes,
intentions and emotional experiences count. This
is empowering for many individuals who often feel
overwhelmed by the current negative predictions and
conicts on the planet. It helps them realize that their
actions and intentions can make a difference and that
by increasing their own coherence, they can become
99
© Copyright 2015 HeartMath Institute
coherence builders and make a contribution that can
help accelerate the shift that many now perceive to
be occurring.
The personal benets of better emotion self-regula-
tion, enhanced well-being, more self-responsibility,
better health and improved relationships people
experience are powerful motivators that reinforce
the process for the individual. As more and more
individuals become increasingly self-regulated and
grow in conscious awareness, the increased individual
coherence in turn increases social coherence, which
is reected in increased cooperation and effective co-
creative initiatives for the benet of society and the
planet. From our perspective, a shift in consciousness
is necessary to achieve new levels of cooperation and
collaboration in the kind of innovative problem-solving
and intuitive discernment required for addressing our
social, environmental and economic problems. In time,
increasing global coherence will be indicated by more
and more communities, states and countries adopting
a more coherent planetary view.
CONCLUSIONS
An ongoing goal of GCI is to further the study of in-
terconnectedness between humanity and the earth’s
energetic systems. GCI conducts research on the
mechanisms of how the earth’s elds affect human
mental and emotional processes, health outcomes
and collective human behavior and explore how
collective human emotions and intentions may be
carried by the earth’s electromagnetic and energetic
elds. Toward these goals, as previously explained,
our global network of ultrasensitive magnetic eld
detectors, specifically designed to measure the
magnetic resonances in the earth/ionosphere cavity
and resonances and Earth’s geomagnetic eld line
resonances are being installed at strategic locations
around the globe. We are hopeful our efforts will pro-
mote and contribute to a deeper understanding of the
mechanisms by which human health and behaviors
are modulated by the earth’s geomagnetic elds and
further clarify which aspects of the eld environment
mediate the varied and specic effects.
Data from the Interconnectedness Study and HRV stud-
ies are yielding promising results and add to the body
of evidence that humans are affected by planetary
energetic elds. GCI hypothesizes that human emo-
tions and consciousness interact with and encode
information in planetary energetic elds, including the
geomagnetic eld, thereby communicating informa-
tion nonlocally between people at a subconscious
level, which, in effect, links all living systems and gives
rise to a form of collective consciousness. Thus, a
feedback loop exists among all human beings and
the earth’s energetic systems.
The essence of the hypothesis is that when enough
individuals and social groups increase their coherence
and utilize it to intentionally create a more coherent
standing reference wave in the global eld, it will help
to lift global consciousness. This can be achieved
when an increasing ratio of people move toward more
balanced and self-regulated emotions and responses.
This in turn can help promote cooperation and collabo-
ration in innovative problem-solving and intuitive dis-
cernment for addressing society’s signicant social,
environmental and economic problems. In time, as
more individuals stabilize the global eld and families,
workplaces and communities, etc., achieve increased
social coherence, global coherence will increase.
This will be indicated by countries adopting a more
coherent planetary view that will lead them to address
social and economic oppression, warfare, cultural
intolerance, crime and disregard for the environment
in more meaningful and successful ways.
Chapter 11: Global Coherence Research: Human-Earth Interconnectivity
100
© Copyright 2015 HeartMath Institute
Science of the Heart
BIBLIOGRAPHY
16. Kukanova, B. and B. Mravec, Complex intracardiac nervous
system. Bratisl Lek Listy, 2006. 107(3): p. 45-51.
17. Armour, J.A., Peripheral autonomic neuronal interactions in
cardiac regulation, in Neurocardiology, J.A. Armour and J.L.
Ardell, Editors. 1994, Oxford University Press: New York. p.
219-244.
18. Cantin, M. and J. Genest, The heart as an endocrine gland.
Pharmacol Res Commun, 1988. 20 Suppl 3: p. 1-22.
19. Strohle, A., et al., Atrial natriuretic hormone decreases endo-
crine response to a combined dexamethasone-corticotropin-
releasing hormone test. Biol Psychiatry, 1998. 43(5): p. 371-5.
20. Butler, G.C., B.L. Senn, and J.S. Floras, Influence of atrial
natriuretic factor on heart rate variability in normal men. Am J
Physiol, 1994. 267(2 Pt 2): p. H500-5.
21. Vollmar, A.M., et al., A possible linkage of atrial natriuretic
peptide to the immune system. Am J Hypertens, 1990. 3(5
Pt 1): p. 408-11.
22. Telegdy, G., The action of ANP, BNP and related peptides on
motivated behavior in rats. Reviews in the Neurosciences,
1994. 5(4): p. 309-315.
23. Huang, M., et al., Identification of novel catecholamine-
containing cells not associated with sympathetic neurons in
cardiac muscle. Circulation, 1995. 92(8(Suppl)): p. I-59.
24. Gutkowska, J., et al., Oxytocin is a cardiovascular hormone.
Brazilian Journal of Medical and Biological Research, 2000.
33: p. 625-633.
25. Hilton, J., On the Influence of Mechanical and Physiological
Rest1863, london: Bell and Daldy.
26. Shapiro, A.P., Hypertension and Stress: A Unied Concept1996,
Mahwah, NJ: Lawrence Erlbaum Associates.
27. Fauvel, J.P., et al., Mental stress-induced increase in blood
pressure is not related to baroreflex sensitivity in middle-aged
healthy men. Hypertension, 2000. 35(4): p. 887-91.
28. Freeman, L.J., et al., Psychological stress and silent myocardial
ischemia. Am Heart J, 1987. 114(3): p. 477-82.
29. Lecomte, D., P. Fornes, and G. Nicolas, Stressful events as a
trigger of sudden death: a study of 43 medico- legal autopsy
cases [see comments]. Forensic Sci Int, 1996. 79(1): p. 1-10.
30. Aboa-Eboule, C., et al., Job strain and risk of acute recurrent
coronary heart disease events. Jama, 2007. 298(14): p. 1652-
60.
31. Henry, J.P., Mechanisms by which stress can lead to coronary
heart disease. Postgrad Med J, 1986. 62(729): p. 687-93.
32. Cas, L.D., et al., [Stress and ischemic heart disease]. Cardio-
logia, 1993. 38(12 Suppl 1): p. 415-25.
33. Brunckhorst, C.B., et al., [Stress, depression and cardiac ar-
rhythmias]. Ther Umsch, 2003. 60(11): p. 673-81.
1. Gahery, Y. and D. Vigier, Inhibitory effects in the cuneate nu-
cleus produced by vago-aortic afferent bers. Brain Research,
1974. 75: p. 241-246.
2. Wölk, C. and M. Velden, Detection variability within the car-
diac cycle: Toward a revision of the ‘baroreceptor hypothesis’.
Journal of Psychophysiology, 1987. 1: p. 61-65.
3. Wölk, C. and M. Velden, Revision of the baroreceptor hypoth-
esis on the basis of the new cardiac cycle effect, in Psychobiol-
ogy: Issues and Applications, N.W. Bond and D.A.T. Siddle, Edi-
tors. 1989, Elsevier Science Publishers B.V.: North-Holland.
p. 371-379.
4. Lane, R.D., et al., Activity in medial prefrontal cortex correlates
with vagal component of heart rate variability during emotion.
Brain and Cognition, 2001. 47: p. 97-100.
5. McCraty, R., Atkinson, M., Tomasino, D., & Bradley, R. T, The
coherent heart: Heart-brain interactions, psychophysiological
coherence, and the emergence of system-wide order. Integral
Review, 2009. 5(2): p. 10-115.
6. McCraty, R., M. Atkinson, and R.T. Bradley, Electrophysi-
ological evidence of intuition: Part 2. A system-wide process?
J Altern Complement Med, 2004. 10(2): p. 325-36.
7. Svensson, T.H. and P. Thoren, Brain noradrenergic neurons in
the locus coeruleus: Inhibition by blood volume load through
vagal afferents. Brain Research, 1979. 172(1): p. 174-178.
8. Schandry, R. and P. Montoya, Event-related brain potentials
and the processing of cardiac activity. Biological Psychology,
1996. 42: p. 75-85.
9. Montoya, P., R. Schandry, and A. Muller, Heartbeat evoked
potentials (HEP): Topography and influence of cardiac aware-
ness and focus of attention. Electroencephalography and
Clinical Neurophysiology, 1993. 88: p. 163-172.
10. Zhang, J.X., R.M. Harper, and R.C. Frysinger, Respiratory
modulation of neuronal discharge in the central nucleus of
the amygdala during sleep and waking states. Experimental
Neurology, 1986. 91: p. 193-207.
11. Armour, J.A., Anatomy and function of the intrathoracic neu-
rons regulating the mammalian heart, in Reflex Control of the
Circulation, I.H. Zucker and J.P. Gilmore, Editors. 1991, CRC
Press: Boca Raton. p. 1-37.
12. Armour, J.A., Potential clinical relevance of the ‘little brain’ on
the mammalian heart. Exp Physiol, 2008. 93(2): p. 165-76.
13. Armour, J.A., Neurocardiology--Anatomical and functional prin-
ciples2003, Boulder Creek, CA: HeartMath Research Center,
HeartMath Institute, Publication No. 03-011.
14. Armour, J.A. and J.L. Ardell, eds. Neurocardiology. 1994,
Oxford University Press: New York.
15. Cameron, O.G., Visceral Sensory Neuroscience: Intercep-
tion2002, New York: Oxford University Press.
101
© Copyright 2015 HeartMath Institute
34. Kageyama, T., et al., Self-reported sleep quality, job stress, and
daytime autonomic activities assessed in terms of short-term
heart rate variability among male white-collar workers. Ind
Health, 1998. 36(3): p. 263-72.
35. Chandola, T., E. Brunner, and M. Marmot, Chronic stress at
work and the metabolic syndrome: prospective study. Bmj,
2006. 332(7540): p. 521-5.
36. Grith, L.S., B.J. Field, and P.J. Lustman, Life stress and
social support in diabetes: association with glycemic control.
Int J Psychiatry Med, 1990. 20(4): p. 365-72.
37. Delamater, A.M., et al., Stress and coping in relation to meta-
bolic control of adolescents with type I diabetes. Journal of
Developmental Behavioral Pediatrics, 1987. 8: p. 136-140.
38. Goldstein, D.S., Stress, allostatic load, catecholamines, and
other neurotransmitters in neurodegenerative diseases. Endocr
Regul, 2011. 45(2): p. 91-8.
39. Frese, M., Stress at work and psychosomatic complaints: a
causal interpretation. Journal of Applied Psychology, 1985.
70(2): p. 314.
40. Gaines, J. and J. Jermier, Emotional exhaustion in a high stress
organization. Academy of Management Journal, 1983. 26(4):
p. 567-586.
41. Fowers, B., Perceived control, illness status, stress and adjust-
ment to cardiac illness. Journal of Psychology, 1994. 128(5):
p. 567-579.
42. Brotman, D.J., S.H. Golden, and I.S. Wittstein, The cardiovas-
cular toll of stress. Lancet, 2007. 370(9592): p. 1089-100.
43. Marchand, A. and P. Durand, Psychological distress, depres-
sion, and burnout: similar contribution of the job demand-
control and job demand-control-support models? J Occup
Environ Med, 2011. 53(2): p. 185-9.
44. Fredrickson, B.L., Positive emotions, in Handbook of Positive
Psychology, C.R. Snyder and S.J. Lopez, Editors. 2002, Oxford
University Press: New York. p. 120-134.
45. Isen, A.M., Positive affect, in Handbook of Cognition and Emo-
tion, T. Dalgleish and M. Power, Editors. 1999, John Wiley &
Sons: New York. p. 522-539.
46. Wichers, M.C., et al., Evidence that moment-to-moment varia-
tion in positive emotions buffer genetic risk for depression: a
momentary assessment twin study. Acta Psychiatr Scand,
2007. 115(6): p. 451-7.
47. Fredrickson, B.L., The role of positive emotions in positive
psychology. The broaden-and-build theory of positive emotions.
American Psychologist, 2001. 56(3): p. 218-226.
48. Fredrickson, B.L. and T. Joiner, Positive emotions trigger
upward spirals toward emotional well-being. Psychological
Science, 2002. 13(2): p. 172-175.
49. Fredrickson, B.L., et al., What good are positive emotions in
crises? A prospective study of resilience and emotions following
the terrorist attacks on the United States on September 11th,
2001. Journal of Personality and Social Psychology, 2003.
84(2): p. 365-376.
50. McCraty, R. and D. Tomasino, Emotional stress, positive emo-
tions, and psychophysiological coherence, in Stress in Health
and Disease, B.B. Arnetz and R. Ekman, Editors. 2006, Wiley-
VCH: Weinheim, Germany. p. 342-365.
51. McCraty, R., et al., The effects of emotions on short-term power
spectrum analysis of heart rate variability. Am J Cardiol, 1995.
76(14): p. 1089-93.
52. Rein, G., M. Atkinson, and R. McCraty, The physiological and
psychological effects of compassion and anger. Journal of
Advancement in Medicine, 1995. 8(2): p. 87-105.
53. McCraty, R. and M. Atkinson, Resilence Training Program
Reduces Physiological and Psychological Stress in Police Of-
cers. Global Advances in Health and Medicne, 2012. 1(5):
p. 44-66.
54. Luthar, S.S., D. Cicchetti, and B. Becker, The construct of
resilience: a critical evaluation and guidelines for future work.
Child Dev, 2000. 71(3): p. 543-62.
55. Lieberman, M.D., Social cognitive neuroscience: A review of
core processes, in Annual Review of Psychology2007, Annual
Reviews: Palo Alto. p. 259-289.
56. Baumeister, R.F., et al., Self-regulation and personality: how
interventions increase regulatory success, and how depletion
moderates the effects of traits on behavior. J Pers, 2006. 74(6):
p. 1773-801.
57. Antonovksy, A., Unraveling The Mystery of Health: How People
Manage Stress and Stay Well. San Francisco: Jossey-Bass,
1987. Cited in: Tresolini, CP and the Pew-Fetzer Task Force.
“Health Professions Education and Relationship-Centered Care”
San Francisco: Pew Health Professions Commission and the
Fetzer Institute, 1994 p. 15.1987.
58. McCraty, R. and M. Zayas, Cardiac coherence, self-regulation,
autonomic stability, and psychosocial well-being. Frontiers in
Psychology, 2014. 5(September ): p. 1-13.
59. McCraty, R., Childre, D, Coherence: Bridging Personal, Social
and Global Health. Alternative Therapies in Health and Medi-
cine, 2010. 16(4): p. 10-24.
60. Nerurkar, A., et al., When physicians counsel about stress:
results of a national study. JAMA Intern Med, 2013. 173(1):
p. 76-7.
61. Avey, H., et al., Health care providers’ training, perceptions, and
practices regarding stress and health outcomes. J Natl Med
Assoc, 2003. 95(9): p. 833, 836-45.
62. Cummings, N.A. and G.R. VandenBos, The twenty years
Kaiser-Permanente experience with psychotherapy and medical
utilization: implications for national health policy and national
health insurance. Health Policy Q, 1981. 1(2): p. 159-75.
63. Grossarth-Maticek, R. and H.J. Eysenck, Self-regulation and
mortality from cancer, coronary heart disease and other causes:
Bibliography
102
© Copyright 2015 HeartMath Institute
Science of the Heart
A prospective study. Personality and Individual Differences,
1995. 19(6): p. 781-795.
64. Pressman, S.D., M.W. Gallagher, and S.J. Lopez, Is the
emotion-health connection a “rst-world problem”? Psychol
Sci, 2013. 24(4): p. 544-9.
65. Mittleman, M.A., et al., Triggering of acute myocardial infarc-
tion onset by episodes of anger. Determinants of Myocardial
Infarction Onset Study Investigators. Circulation, 1995. 92(7):
p. 1720-5.
66. Lyubomirsky, S., L. King, and E. Diener, The benets of frequent
positive affect: does happiness lead to success? Psychol Bull,
2005. 131(6): p. 803-55.
67. Danner, D.D., D.A. Snowdon, and W.V. Friesen, Positive emo-
tions in early life and longevity: Findings from the nun study.
Journal of Personality and Social Psychology, 2001. 80(5):
p. 804-813.
68. Kawachi, I., et al., Prospective study of phobic anxiety and risk
of coronary heart disease in men. Circulation, 1994. 89(5): p.
1992-7.
69. Grossarth-Maticek, R. and H.J. Eysenck, Creative novation
behaviour therapy as a prophylactic treatment for cancer and
coronary heart disease: Part I--Description of treatment [pub-
lished erratum appears in Behav Res Ther 1993 May;31(4):437]
[see comments]. Behav Res Ther, 1991. 29(1): p. 1-16.
70. Kubzansky, L.D., et al., Is worrying bad for your heart? A
prospective study of worry and coronary heart disease in the
Normative Aging Study. Circulation, 1997. 95(4): p. 818-824.
71. Rosenman, R.H., The independent roles of diet and serum lipids
in the 20th-century rise and decline of coronary heart disease
mortality. Integr Physiol Behav Sci, 1993. 28(1): p. 84-98.
72. Penninx, B.W., et al., Effects of social support and personal
coping resources on mortality in older age: the Longitudinal
Aging Study Amsterdam. Am J Epidemiol, 1997. 146(6): p.
510-9.
73. Allison, T.G., et al., Medical and economic costs of psychologic
distress in patients with coronary artery disease. Mayo Clinic
Proceedings, 1995. 70(8): p. 734-742.
74. Eysenck, H.J., Personality, stress and cancer: Prediction and
prophylaxis. British Journal of Medical Psychology, 1988.
61(Pt 1): p. 57-75.
75. Thomas, S.A., et al., Psychosocial factors and survival in the
cardiac arrhythmia suppression trial (CAST): a reexamination.
Am J Crit Care, 1997. 6(2): p. 116-126.
76. Siegman, A.W., et al., Dimensions of anger and CHD in men
and women: self-ratings versus spouse ratings. J Behav Med,
1998. 21(4): p. 315-36.
77. Carroll, D., et al., Blood pressure reactions to the cold pressor
test and the prediction of ischaemic heart disease: data from
the Caerphilly Study. Journal of Epidemiology and Community
Health, 1998. 52: p. 528-529.
78. Dolcos, F., A.D. Iordan, and S. Dolcos, Neural correlates of
emotion-cognition interactions: A review of evidence from brain
imaging investigations. J Cogn Psychol (Hove), 2011. 23(6):
p. 669-694.
79. Damasio, A.R., Descartes’ Error: Emotion, Reason and the Hu-
man Brain1994, New York: G.P. Putnam’s Sons.
80. Goleman, D., Emotional Intelligence1995, New York: Bantam
Books.
81. McCraty, R. and D. Childre, Coherence: bridging personal, so-
cial, and global health. Altern Ther Health Med, 2010. 16(4):
p. 10-24.
82. Porges, S.W., The polyvagal perspective. Biol Psychol, 2007.
74(2): p. 116-43.
83. Shaffer, F., R. McCraty, and C. Zerr, A healthy heart is not a
metronome: An integrative review of the heart’s anatomy and
heart rate variability. Frontiers in Psychology, 2014. 5:1040.
84. Singer, D.H., et al., Low heart rate variability and sudden cardiac
death. Journal of Electrocardiology, 1988(Supplemental is-
sue): p. S46-S55.
85. Singer, D.H., High heart rate variability, marker of healthy lon-
gevity. Am J Cardiol, 2010. 106(6): p. 910.
86. Geisler, F.C., et al., Cardiac vagal tone is associated with social
engagement and self-regulation. Biol Psychol, 2013. 93(2): p.
279-86.
87. Reynard, A., et al., Heart rate variability as a marker of self-
regulation. Appl Psychophysiol Biofeedback, 2011. 36(3):
p. 209-15.
88. Segerstrom, S.C. and L.S. Nes, Heart rate variability reflects
self-regulatory strength, effort, and fatigue. Psychol Sci, 2007.
18(3): p. 275-81.
89. Thayer, J.F., et al., Heart rate variability, prefrontal neural func-
tion, and cognitive performance: the neurovisceral integration
perspective on self-regulation, adaptation, and health. Ann
Behav Med, 2009. 37(2): p. 141-53.
90. Camm, A.J., et al., Heart rate variability standards of measure-
ment, physiological interpretation, and clinical use. Task Force
of the European Society of Cardiology and the North American
Society of Pacing and Electrophysiology. Circulation, 1996.
93(5): p. 1043-1065.
91. Hon, E.H. and S.T. Lee, Electronic evaluations of the fetal heart
rate patterns preceeding fetal death: further observations.
American Journal of Obstetric Gynecology, 1965. 87: p.
814-826.
92. Braune, H.J. and U. Geisendorfer, Measurement of heart
rate variations: influencing factors, normal values and
diagnostic impact on diabetic autonomic neuropathy.
Diabetes Res Clin Pract, 1995. 29(3): p. 179-87.
93. Vinik, A.I., et al., Diabetic autonomic neuropathy. Diabetes
Care, 2003. 26(5): p. 1553-79.
103
© Copyright 2015 HeartMath Institute
94. Ewing, D., I. Campbell, and B. Clarke, Mortality in diabetic
autonomic neuropathy. Lancet, 1976. 1: p. 601-603.
95. Wolf, M.M., et al., Sinus arrhythmia in acute mycardial infarc-
tion. Medical Journal of Australia, 1978. 2: p. 52-53.
96. Umetani, K., et al., Twenty-four hour time domain heart rate
variability and heart rate: relations to age and gender over nine
decades. J Am Coll Cardiol, 1998. 31(3): p. 593-601.
97. Dekker, J.M., et al., Heart rate variability from short electro-
cardiographic recordings predicts mortality from all causes in
middle-aged and elderly men. The Zutphen Study. American
Journal of Epidemiology, 1997. 145(10): p. 899-908.
98. Tsuji, H., et al., Reduced heart rate variability and mortality risk
in an elderly cohort. The Framingham Heart Study. Circulation,
1994. 90(2): p. 878-883.
99. Berntson, G.G., et al., Cardiac autonomic balance versus car-
diac regulatory capacity. Psychophysiology, 2008. 45(4): p.
643-52.
100. Beauchaine, T., Vagal tone, development, and Gray’s motiva-
tional theory: toward an integrated model of autonomic nervous
system functioning in psychopathology. Dev Psychopathol,
2001. 13(2): p. 183-214.
101. Geisler, F. and T. Kubiak, Heart rate variability predicts self‐con-
trol in goal pursuit. European Journal of Personality, 2009.
23(8): p. 623-633.
102. Appelhans, B. and L. Luecken, Heart Rate Variability as an
Index of Regulated Emotional Responding. Review of General
Psychology, 2006. 10(3): p. 229-240.
103. Geisler, F., et al., The impact of heart rate variability on subjec-
tive well-being is mediated by emotion regulation. Personality
and Individual Differences, 2010. 49(7): p. 723-728.
104. Smith, T.W., et al., Matters of the variable heart: respiratory
sinus arrhythmia response to marital interaction and associa-
tions with marital quality. J Pers Soc Psychol, 2011. 100(1):
p. 103-19.
105. Nasermoaddeli, A., M. Sekine, and S. Kagamimori, Associa-
tion between sense of coherence and heart rate variability in
healthy subjects. Environ Health Prev Med, 2004. 9(6): p.
272-4.
106. Zohar, A., R. Cloninger, and R. McCraty, Personality and Heart
Rate Variability: Exploring Pathways from Personality to Cardiac
Coherence and Health. Open Journal of Social Sciences, 2013.
1(6): p. 32-39.
107. Ramaekers, D., et al., Association between cardiac autonomic
function and coping style in healthy subjects. Pacing Clin
Electrophysiol, 1998. 21(8): p. 1546-52.
108. Lloyd, A., Brett, D., Wesnes, K., Coherence Training Improves
Cognitive Functions and Behavior In Children with ADHD.
Alternative Therapies in Health and Medicine, 2010. 16(4):
p. 34-42.
109. Ginsberg, J.P., Berry, M.E., Powell, D.A., Cardiac Coherence and
PTSD in Combat Veterans. Alternative Therapies in Health and
Medicine, 2010. 16(4): p. 52-60.
110. Bradley, R.T., et al., Emotion self-regulation, psychophysi-
ological coherence, and test anxiety: results from an experiment
using electrophysiological measures. Appl Psychophysiol
Biofeedback, 2010. 35(4): p. 261-83.
111. Lehrer, P.M., et al., Heart rate variability biofeedback increases
baroreflex gain and peak expiratory flow. Psychosomatic
Medicine, 2003. 65(5): p. 796-805.
112. Bedell, W., Coherence and hearlth care cost - RCA acturial
study: A cost-effectivness cohort study Alternative Therapies
in Health and Medicine, 2010. 16(4): p. 26-31.
113. Alabdulgader, A., Coherence: A Novel Nonpharmacological
Modality for Lowering Blood Pressure in Hypertensive Patients.
Global Advances in Health and Medicne, 2012. 1(2): p. 54-62.
114. McCraty, R., et al., New hope for correctional ofcers: an in-
novative program for reducing stress and health risks. Appl
Psychophysiol Biofeedback, 2009. 34(4): p. 251-72.
115. McCraty, R., M. Atkinson, and D. Tomasino, Impact of a
workplace stress reduction program on blood pressure and
emotional health in hypertensive employees. J Altern Comple-
ment Med, 2003. 9(3): p. 355-69.
116. McCraty, R., et al., The impact of a new emotional self-man-
agement program on stress, emotions, heart rate variability,
DHEA and cortisol. Integr Physiol Behav Sci, 1998. 33(2): p.
151-70.
117. Oppenheimer, S. and D. Hopkins, Suprabulbar neuronal regu-
lation of the heart, in Neurocardiology, J.A. Armour and J.L.
Ardell, Editors. 1994, Oxford University Press: New York. p.
309-341.
118. Hopkins, D. and H. Ellenberger, Cardiorespiratory neurons
in the mudulla oblongata: Input and output relationhsips, in
Neurocardiology, J.A. Armour and J.L. Ardell, Editors. 1994,
Oxford University Press: New York. p. 219-244.
119. Beaumont, E., et al., Network interactions within the canine
intrinsic cardiac nervous system: implications for reflex control
of regional cardiac function. J Physiol, 2013. 591(Pt 18): p.
4515-33.
120. Hainsworth, R., The control and physiological importance on
heart rate, in Heart Rate Variability, M. Malik and A.J. Camm,
Editors. 1995, Futura Publishing COmpany, Inc.: Armonk NY.
p. 3-19.
121. Palatini, P., Elevated heart rate as a predictor of increased
cardiovascular morbidity. J Hypertens Suppl, 1999. 17(3): p.
S3-10.
122. Stampfer, H.G., The relationship between psychiatric illness
and the circadian pattern of heart rate. Aust N Z J Psychiatry,
1998. 32(2): p. 187-98.
Bibliography
104
© Copyright 2015 HeartMath Institute
Science of the Heart
123. Stampfer, H.G. and S.B. Dimmitt, Variations in circadian heart
rate in psychiatric disorders: theoretical and practical implica-
tions. ChronoPhysiology and Therapy, 2013. 3: p. 41–50.
124. Opthof, T., The normal range and determinants of the intrinsic
heart rate in man. Cardiovasc Res, 2000. 45(1): p. 177-84.
125. Umetani, K., C.L. Duda, and D.H. Singer. Aging effects on
cycle length dependence of heart rate variability. in Biomedical
Engineering Conference, 1996. 1996. Proceedings of the 1996
Fifteenth Southern. IEEE.
126. Electrophysiology, T.F.o.t.E.S.o.C.a.t.N.A.S.o.P.a., Heart rate
variability: Standards of measurement, physiological interpreta-
tion, and clinical use. Circulation, 1996. 93: p. 1043-1065.
127. Hirsch, J.A. and B. Bishop, Respiratory sinus arrhythmia in
humans: How breathing pattern modulates heart rate. Ameri-
can Journal of Physiology, 1981. 241(4): p. H620-H629.
128. Eckberg, D.L., Human sinus arrhythmia as an index of vagal
outflow. Journal of Applied Physiology, 1983. 54: p. 961-966.
129. Malliani, A., Association of Heart Rate Variability components
with physiological regulatory mechanisms, in Heart Rate
Variability, M. Malik and A.J. Camm, Editors. 1995, Futura
Publishing COmpany, Inc.: Armonk NY. p. 173-188.
130. deBoer, R.W., J.M. Karemaker, and J. Strackee, Hemodynamic
fluctuations and baroreflex sensitivity in humans: a beat-to-beat
model. Am J Physiol, 1987. 253(3 Pt 2): p. H680-9.
131. Baselli, G., et al., Model for the assessment of heart period
variability interactions of respiration influences. Medical and
Biological Engineering and Computing, 1994. 32(2): p. 143-
152.
132. Ahmed, A.K., J.B. Harness, and A.J. Mearns, Respiratory
Control of Heart Rate. Eur J Appl Physiol, 1982. 50: p. 95-104.
133. Tiller, W.A., R. McCraty, and M. Atkinson, Cardiac coherence: a
new, noninvasive measure of autonomic nervous system order.
Altern Ther Health Med, 1996. 2(1): p. 52-65.
134. Brown, T.E., et al., Important influence of respiration on human
R-R interval power spectra is largely ignored. J Appl Physiol
(1985), 1993. 75(5): p. 2310-7.
135. Malliani, A., et al., Power spectral analysis of cardiovascular
variability in patients at risk for sudden cardiac death. J Car-
diovasc Electrophysiol, 1994. 5(3): p. 274-86.
136. Pal, G.K., et al., Sympathovagal imbalance contributes to
prehypertension status and cardiovascular risks attributed by
insulin resistance, inflammation, dyslipidemia and oxidative
stress in rst degree relatives of type 2 diabetics. PLoS One,
2013. 8(11): p. e78072.
137. Pagani, M., F. Lombardi, and S. Guzzette, Power spectral
analysis of heart rate and arterial pressure variabilities as a
marker of sympatho-vagal interaction in man and conscious
dog. Circulation Research, 1986. 59: p. 178-184.
138. Axelrod, S., et al., Spectral analysis of fluctuations in heart
rate: An objective evaluation. Nephron, 1987. 45: p. 202-206.
139. Schmidt, H., et al., Autonomic dysfunction predicts mortality in
patients with multiple organ dysfunction syndrome of different
age groups. Crit Care Med, 2005. 33(9): p. 1994-2002.
140. Hadase, M., et al., Very low frequency power of heart rate vari-
ability is a powerful predictor of clinical prognosis in patients
with congestive heart failure. Circ J, 2004. 68(4): p. 343-7.
141. Tsuji, H., et al., Impact of reduced heart rate variability on risk
for cardiac events. The Framingham Heart Study. Circulation,
1996. 94(11): p. 2850-5.
142. Bigger, J.T., Jr., et al., Frequency domain measures of heart
period variability and mortality after myocardial infarction.
Circulation, 1992. 85(1): p. 164-71.
143. Shah, A.J., et al., Posttraumatic stress disorder and impaired
autonomic modulation in male twins. Biol Psychiatry, 2013.
73(11): p. 1103-10.
144. Lampert, R., et al., Decreased heart rate variability is associ-
ated with higher levels of inflammation in middle-aged men.
Am Heart J, 2008. 156(4): p. 759 e1-7.
145. Carney, R.M., et al., Heart rate variability and markers of inflam-
mation and coagulation in depressed patients with coronary
heart disease. J Psychosom Res, 2007. 62(4): p. 463-7.
146. Theorell, T., et al., Saliva testosterone and heart rate variability
in the professional symphony orchestra after “public faintings”
of an orchestra member. Psychoneuroendocrinology, 2007.
32(6): p. 660-8.
147. Kleiger, R.E., P.K. Stein, and J.T. Bigger, Jr., Heart rate vari-
ability: measurement and clinical utility. Ann Noninvasive
Electrocardiol, 2005. 10(1): p. 88-101.
148. Akselrod, S., et al., Power spectrum analysis of heart rate
fluctuation: a quantitative probe of beat-to-beat cardiovascular
control. Science, 1981. 213(10): p. 220-222.
149. Cerutti, S., A.M. Bianchi, and L.T. Mainardi, Spectral analysis
of the heart rate variability signal, in Heart Rate Variability,
M. Malik and A.J. Camm, Editors. 1995, Futura Publishing
COmpany, Inc.: Armonk NY. p. 63-74.
150. Murphy, D.A., et al., The heart reinnervates after transplanta-
tion. Ann Thorac Surg, 2000. 69(6): p. 1769-81.
151. Ramaekers, D., et al., Heart rate variability after cardiac trans-
plantation in humans. Pacing Clin Electrophysiol, 1996. 19(12
Pt 1): p. 2112-9.
152. Kember, G., et al., Competition model for aperiodic stochastic
resonance in a Fitzhugh-Nagumo model of cardiac sensory
neurons. Physical Review E, 2001. 63(4 Pt 1): p. 041911.
153. Kember, G.C., et al., Aperiodic stochastic resonance in a
hysteretic population of cardiac neurons. Physical Review E,
2000. 61(2): p. 1816-1824.
154. Berntson, G.G., et al., Heart rate variability: origins, methods,
and interpretive caveats. Psychophysiology, 1997. 34(6): p.
623-48.
105
© Copyright 2015 HeartMath Institute
155. Huikuri, H.V., et al., Circadian rhythms of frequency domain
measures of heart rate variability in healthy subjects and
patients with coronary artery disease. Effects of arousal and
upright posture. Circulation, 1994. 90(1): p. 121-6.
156. Singh, R.B., et al., Circadian heart rate and blood pressure vari-
ability considered for research and patient care. Int J Cardiol,
2003. 87(1): p. 9-28; discussion 29-30.
157. Bernardi, L., et al., Physical activity influences heart rate
variability and very-low-frequency components in Holter elec-
trocardiograms. Cardiovasc Res, 1996. 32(2): p. 234-7.
158. Stein, P.K., et al., Traditional and nonlinear heart rate variability
are each independently associated with mortality after myocar-
dial infarction. J Cardiovasc Electrophysiol, 2005. 16(1): p.
13-20.
159. Kleiger, R.E., et al., Decreased heart rate variability and its
association with increased mortality after acute myocardial
infarction. American Journal of Cardiology, 1987. 59(4): p.
256-262.
160. Damasio, A., Looking for Spinoza: Joy, Sorrow, and the Feeling
Brain2003, Orlando: Harcourt.
161. Stein, J., ed. The Random House College Dictionary. 1975,
Random House: New York. 261.
162. Strogatz, S. and I. Stewart, Coupled Oscillators and Biological
Synchronization. Scientic American, 1993(December): p.
102-109.
163. Tiller, W.A., R. McCraty, and M. Atkinson, Cardiac coherence: A
new, noninvasive measure of autonomic nervous system order.
Alternative Therapies in Health and Medicine, 1996. 2(1): p.
52-65.
164. Bradley, R.T. and K.H. Pribram, Communication and stabil-
ity in social collectives. Journal of Social and Evolutionary
Systems, 1998. 21(1): p. 29-80.
165. Ho, M.-W., The Rainbow and the Worm: The Physics of Organ-
isms2005, Singapore: World Scientic Publishing Co.
166. Leon, E., et al., Affect-aware behavior modelling and control
inside an intelligent environment Pervasive and Mobile
Computing doi:10.1016/j.pmcj.2009.12.002, 2010. 167.
Hasan, Y., L. Begue, and B.J. Bushman, Violent video games
stress people out and make them more aggressive. Aggress
Behav, 2013. 39(1): p. 64-70.
168. McCraty, R., et al., The effects of emotions on short-term power
spectrum analysis of heart rate variability. American Journal
of Cardiology, 1995. 76(14): p. 1089-1093.
169. Pribram, K.H. and F.T. Melges, Psychophysiological basis of
emotion, in Handbook of Clinical Neurology, P.J. Vinken and
G.W. Bruyn, Editors. 1969, North-Holland Publishing Com-
pany: Amsterdam. p. 316-341.
170. Bradley, R.T., Charisma and Social Structure: A Study of Love
and Power, Wholeness and Transformation1987, New York:
Paragon House.
171. LeDoux, J., The Emotional Brain: The Mysterious Underpinnings
of Emotional Life1996, New York: Simon and Schuster.
172. Miller, G.A., E.H. Galanter, and K.H. Pribram, Plans and the
Structure of Behavior1960, New York: Henry Holt & Co.
173. Pribram, K.H., Feelings as monitors, in Feelings and Emotions,
M.B. Arnold, Editor 1970, Academic Press: New York. p. 41-
53.
174. Olatunji, B.O., et al., Heightened attentional capture by threat
in veterans with PTSD. J Abnorm Psychol, 2013. 122(2): p.
397-405.
175. Pribram, K.H. and D. McGuinness, Arousal, activation, and
effort in the control of attention. Psychological Review, 1975.
82(2): p. 116-149.
176. Pribram, K.H., Languages of the Brain: Experimental Paradoxes
and Principals in Neuropsychology1971, New York: Brandon
House.
177. Frysinger, R.C. and R.M. Harper, Cardiac and respiratory cor-
relations with unit discharge in epileptic human temporal lobe.
Epilepsia, 1990. 31(2): p. 162-171.
178. Childre, D.L., Freeze-Frame®, Fast Action Stress Relief1994,
Boulder Creek: Planetary Publications.
179. Childre, D. and H. Martin, The HeartMath Solution1999, San
Francisco: HarperSanFrancisco.
180. Childre, D. and B. Cryer, From Chaos to Coherence: The Power
to Change Performance2000, Boulder Creek, CA: Planetary.
181. Childre, D. and D. Rozman, Overcoming Emotional Chaos:
Eliminate Anxiety, Lift Depression and Create Security in Your
Life2002, San Diego: Jodere Group.
182. Childre, D. and D. Rozman, Transforming Stress: The Heart-
Math Solution to Relieving Worry, Fatigue, and Tension2005,
Oakland, CA: New Harbinger Publications.
183. Lehrer, P., et al., Heart rate variability biofeedback: effects of
age on heart rate variability, baroreflex gain, and asthma. Chest,
2006. 129(2): p. 278-84.
184. Ratanasiripong, P., N. Ratanasiripong, and D. Kathalae,
Biofeedback Intervention for Stress and Anxiety among Nurs-
ing Students: A Randomized Controlled Trial. International
Scholarly Research Network Nurs. 2012;2012:827972, 2012.
185. Beckham, A.J., T.B. Greene, and S. Meltzer-Brody, A pilot study
of heart rate variability biofeedback therapy in the treatment
of perinatal depression on a specialized perinatal psychiatry
inpatient unit. Arch Womens Ment Health, 2013. 16(1): p.
59-65.
186. Siepmann, M., et al., A pilot study on the effects of heart
rate variability biofeedback in patients with depression and in
healthy subjects. Appl Psychophysiol Biofeedback, 2008.
33(4): p. 195-201.
187. Hallman, D.M., et al., Effects of heart rate variability biofeed-
back in subjects with stress-related chronic neck pain: a pilot
study. Appl Psychophysiol Biofeedback, 2011. 36(2): p. 71-80.
Bibliography
106
© Copyright 2015 HeartMath Institute
Science of the Heart
188. Henriques, G., et al., Exploring the effectiveness of a computer-
based heart rate variability biofeedback program in reducing
anxiety in college students. Appl Psychophysiol Biofeedback,
2011. 36(2): p. 101-12.
189. Lin, G., et al., Heart rate variability biofeedback decreases blood
pressure in prehypertensive subjects by improving autonomic
function and baroreflex. J Altern Complement Med, 2012.
18(2): p. 143-52.
190. McCraty, R. and D. Tomasino, Coherence-building techniques
and heart rhythm coherence feedback: New tools for stress
reduction, disease prevention, and rehabilitation, in Clinical
Psychology and Heart Disease, E. Molinari, A. Compare, and
G. Parati, Editors. 2006, Springer-Verlag: Milan, Italy.
191. Li, W.-C., et al., The Investigation of Visual Attention and
Workload by Experts and Novices in the Cockpit, in Engineer-
ing Psychology and Cognitive Ergonomics. Applications and
Services, D. Harris, Editor 2013, Springer Berlin Heidelberg.
p. 167-176.
192. Luskin, F., K. Newell, and W. Haskell, Stress management
training of elderly patients with congestive heart failure: pilot
study. Preventive Cardiology, 1999. 2: p. 101-104.
193. Weltman, G., et al., Police Department Personnel Stress Resil-
ience Training: An Institutional Case Study. Global Advances
in Health and Medicne, 2014. 3(2): p. 72-79.
194. Lehrer, P., Y. Sasaki, and Y. Saito, Zazen and cardiac variability.
Psychosomatic Medicine, 1999. 61: p. 812-821.
195. Kim, D.-K., et al., Dynamic correlations between heart and brain
rhythm during Autogenic meditation. Front. Hum. Neurosci.,
2013. 7:414.
196. Peng, C.K., et al., Exaggerated hear t rate oscillations during two
meditation techniques. Int J Cardiol, 1999. 70(2): p. 101-7.
197. Wu, S.D. and P.C. Lo, Inward-attention meditation increases
parasympathetic activity: a study based on heart rate variability.
Biomed Res, 2008. 29(5): p. 245-50.
198. Phongsuphap, S. and Y. Pongsupap, Analysis of Heart Rate
Variability during Meditation by a Pattern Recognition Method
Computing in Cardiology, 2011. 38: p. 197-200.
199. Stanley, R., Types or prayer, heart rate variablity and innate
healing Zygon, 2009. 44(4): p. 825-846.
200. Bernardi, L., et al., Effect of rosary prayer and yoga mantras on
autonomic cardiovascular rhythms: Comparative study. BMJ,
2001. 323: p. 1446-1449.
201. Stanley, R., Types of Prayer, Heart Rate Variablity and Innate
Healing Zygon 2009. 44(4).
202. Lehrer, P., et al., Effects of rhythmical muscle tension at 0.1Hz
on cardiovascular resonance and the baroreflex. Biol Psychol,
2009. 81(1): p. 24-30.
203. Baule, G. and R. McFee, Detection of the magnetic eld of the
heart. American Heart Journal, 1963. 55(7): p. 95-96.
204. Nakaya, Y., Magnetocardiography: a comparison with electro-
cardiography. J Cardiogr Suppl, 1984. 3: p. 31-40.
205. Halberg, F., et al., Cross-spectrally coherent ~10.5- and 21-year
biological and physical cycles, magnetic storms and myocardial
infarctions. Neuroendocrinology, 2000. 21: p. 233-258.
206. Pribram, K.H., Brain and Perception: Holonomy and Structure
in Figural Processing1991, Hillsdale, NJ: Lawrence Erlbaum
Associates, Publishers.
207. Prank, K., et al., Coding of time-varying hormonal signals in
intracellular calcium spike trains. Pac Symp Biocomput, 1998:
p. 633-44.
208. Schofl, C., K. Prank, and G. Brabant, Pulsatile hormone
secretion for control of target organs. Wiener Medizinische
Wochenschrift, 1995. 145(17-18): p. 431-435.
209. Scho, C., et al., Frequency and amplitude enhancement of
calcium transients by cyclic AMP in hepatocytes. Biochem J,
1991. 273(Pt 3): p. 799-802.
210. Coles, M.G.H., G. Gratton, and M. Fabini, Event-related brain
potentials, in Principles of Psychophysiology: Physical, Social
and Inferential Elements, J.T. Cacioppo and L.G. Tassinary,
Editors. 1990, Cambridge University Press: NY.
211. Song, L.Z., G.E. Schwartz, and L.G. Russek, Heart-focused
attention and heart-brain synchronization: Energetic and physi-
ological mechanisms. Alternative Therapies in Health and
Medicine, 1998. 4(5): p. 44-62.
212. McCraty, R., M. Atkinson, and W.A. Tiller, New electrophysi-
ological correlates associated with intentional heart focus.
Subtle Energies, 1993. 4(3): p. 251-268.
213. Russell, P., The Brain Book1979, New York: Penguin Books USA.
214. Hateld, E., Emotional Contagion1994, New York: Cambridge
University Press.
215. McCraty, R., et al. The Electricity of Touch: Detection and
measurment of cardiac energy exchange between people. in
The Fifth Appalachian Conference on Neurobehavioral Dynam-
ics: Brain and Values. 1996. Radford VA: Lawrence Erlbaum
Associates, Inc. Mahwah, NJ.
216. Anshel, M.H., Effect of chronic aerobic exercise and progressive
relaxation on motor performance and affect following acute
stress. Behav Med, 1996. 21(4): p. 186-96.
217. Stroink, G., Principles of cardiomagnetism, in Advances in
Biomagnetism, S.J. Williamson, et al., Editors. 1989, Plenum
Press: New York. p. 47-57.
218. Anshel, M., A conceptual model and implications for coping
wtih stressful events in police work. Criminal Justice and
Behavior, 2000. 27(3): p. 375-400.
219. McCraty, R., Influence of cardiac afferent input on heart-brain
synchronization and cognitive performance. International
Journal of Psychophysiology, 2002. 45(1-2): p. 72-73.
107
© Copyright 2015 HeartMath Institute
220. Holcomb, B.K., et al., Dimethylamino parthenolide enhances the
inhibitory effects of gemcitabine in human pancreatic cancer
cells. J Gastrointest Surg, 2012. 16(7): p. 1333-40.
221. Morris, S.M., Facilitating collective coherence: Group Effects
on Heart Rate Variability Coherence and Heart Rhythm Syn-
chronization. Alternative Therapies in Health and Medicine,
2010. 16(4): p. 62-72.
222. Waters, J.A., et al., Single-port laparoscopic right hemicolec-
tomy: the rst 100 resections. Dis Colon Rectum, 2012. 55(2):
p. 134-9.
223. Nelson, R. Scientic Evidence for the Existence of a True Noo-
sphere: Foundation for a Noo-Constitution. in World Forum of
Spiritual Culture. 2010. Astana, Kazakhstan.
224. Hodgkinson, G.P., J. Langan-Fox, and E. Sadler-Smith, In-
tuition: A fundamental bridging construct in the behavioural
sciences. British Journal of Psychology, 2008. 99(1): p. 1-27.
225. Myers, D.G., Intuition: Its Powers and Perils2002, New Haven:
Yale University Press.
226. Bradley, R.T., et al., Nonlocal Intuition in Entrepreneurs and Non-
entrepreneurs: Results of Two Experiments Using Electrophysi-
ological Measures. International Journal of Entrepreneurship
and Small Business, 2011. 12(3): p. 343-372.
227. Dane, E. and M.G. Pratt, Exploring intuition and its role in
managerial decision making. Academy of Management Re-
view, 2007. 32: p. 33–54.
228. Bastick, T., Intuition: How we think and act1982, New York::
Wiley.
229. Moir, A. and D. Jessel, Brainsex: The real difference between
men and women1989, London:: Mandarin Paperbacks.
230. Larsen, A. and C. Bundesen, A template-matching pandemo-
nium recognizes unconstrained handwritten characters with
high accuracy. Mem Cognit, 1996. 24(2): p. 136-43.
231. Craig, J. and N. Lindsay, Quantifying “gut feeling” in the op-
portunity recognition process. Frontiers of Entrepreneurship
Research, 2001: p. 124-135.
232. Halberg, F., et al., Time Structures (Chronomes) of the Blood
Circulation, Populations’ Health, Human Affairs and Space
Weather. World Heart Journal, 2011. 3(1): p. 1-40.
233. Uyeda, S., et al., Geoelectric potential changes: possible precur-
sors to earthquakes in Japan. Proc Natl Acad Sci U S A, 2000.
97(9): p. 4561-6.
234. Wiseman, R. and M. Schlitz, Experimenter effects and the
remote detection of staring. Journal of Parapsychology, 1997.
61: p. 197-207.
235. Bohm, D. and B.J. Hiley, The Undivided Universe1993, London:
Routledge.
236. Laszlo, E., The Interconnected Universe: Conceptual Founda-
tions of Transdiciplinary Unied Theroy1995, Singapore: World
Scientic.
237. Nadeau, R. and M. Kafatos, The Non-Local Universe: The
New Physics and Matters of the Mind1999, New York: Oxford
University Press.
238. Mayer, R.E., The search for insight: Grappling with gestalt
psychology’s unanswered questions., in The nature of insight,
R.J. Sternberg and J.E. Davidson, Editors. 1996, The MIT
Press: Cambridge, MA. p. 3–32.
239. Hogarth, R.M., Educating Intuition2001, Chicago: The Univer-
sity of Chicago Press.
240. Bem, D.J., Feeling the future: Experimental evidence for anoma-
lous retroactive influences on cognition and affect. J Pers Soc
Psychol, 2011.
241. Radin, D., The Conscious Universe: The Scientic Truth of
Psychic Phenomena1997, San Francisco, CA: HarperEdge.
242. Mossbridge, J., P. Tressoldi, E, and J. Utts Predictive Physio-
logical Anticipation Preceding Seemingly Unpredictable Stimuli:
A Meta-Analysis. Frontiers in Psychology, 2012. 3:390.
243. McCraty, R., M. Atkinson, and R.T. Bradley, Electrophysiologi-
cal evidence of intuition: Part 1. The surprising role of the heart.
Journal of Alternative and Complementary Medicine, 2004.
10(1): p. 133-143.
244. McCraty, R., M. Atkinson, and R.T. Bradley, Electrophysi-
ological evidence of intuition: Part 2. A system-wide process?
Journal of Alternative and Complementary Medicine, 2004.
10(2): p. 325-336.
245. Tressoldi, P.E., et al., Heart rate differences between targets
and non targets in intuition tasks. Fiziol Cheloveka, 2005.
31(6): p. 32-6.
246. Hu, H. and M. Wu, New Nonlocal Biological Effect. NeuroQuan-
tology 2012. 10(3): p. 462-467.
247. Tressoldi, P.E., et al., Implicit Intuition: How Heart Rate can
Contribute to Prediction of Future Events. Journal of the So-
ciety for Psychical research 2009. 73: p. 1-16.
248. Sartori, L., et al., Physiological correlates of ESP: heart rate
differences between targets and nontargets. Journal of Para-
psychology, 2004. 68(2): p. 351.
249. Tressoldi, P.E., et al., Further evidence of the possibility of
exploiting anticipatory physiological signals to assist implicit
intuition of random events. Journal of Scientic Exploration,
2010. 24(3): p. 411.
250. Bradley, R.T., R. McCraty, M. Atkinson, & M. Gillin. Nonlocal In-
tuition in Entrepreneurs and Nonentrepreneurs: An Experimental
Comparison Using Electrophysiological Measures. in Regional
Frontiers of Entrepreneurship Research. 2008. Hawthorne,
Australia.
251. Toroghi, S.R., et al., Nonlocal Intuition: Replication and Paired-
Subjects Enhancement Effects. Global Advances in Health
and Medicne, 2014.
252. McCraty, R., Electrophysiology of Intuition: Pre-stimulus Re-
sponses in Group and Individual Participants Using a Roulette
Bibliography
108
© Copyright 2015 HeartMath Institute
Science of the Heart
Paradigm. Global Advances in Health and Medicne, 2014.
3(2): p. 16-27.
253. Laszlo, E., Quantum Shift in the Global Brain: how the new
scientic reality can change us and our world2008, Rochester,
VT: Inner Traditions.
254. Mitchell, E., Quantum holography: a basis for the interface
between mind and matter, in Bioelectromagnetic Medicine, P.G.
Rosch and M.S. Markov, Editors. 2004, Dekker: New York, NY.
p. 153-158.
255. Tiller, W.A., J. W E Dibble, and M.J. Kohane, Conscious Acts
of Creation: The Emergence of a New Physics2001, Walnut
Creek, CA: Pavior Publishing. (pp. 201-202).
256. Bradley, R.T., Psycholphysiology of Intution: A quantum-
holgraphic theory on nonlocal communication. World Futures:
The Journal of General Evolution, 2007. 63(2): p. 61-97.
257. Marcer, P. and W. Schempp, The brain as a conscious system.
Internationl Journal of General Systems, 1998. 27: p. 231-
248.
258. Pribram, K.H. and R.T. Bradley, The brain, the me and the I, in
Self-Awareness: Its Nature and Development, M. Ferrari and
R. Sternberg, Editors. 1998, The Guilford Press: New York.
p. 273-307.
259. Schempp, W., Quantum holograhy and neurocomputer archi-
tectures. Journal of Mathematical Imaging and vision, 1992.
2: p. 109-164.
260. Simons, D.J. and C.F. Chabris, Gorillas in our midst: Sustained
inattentional blindness for dynamic events. Perception, 1999.
28(9): p. 1059-1074.
261. Baumeister, R.F., Ego depletion and self-regulation failure: a
resource model of self-control. Alcohol Clin Exp Res, 2003.
27(2): p. 281-4.
262. Petitmengin-Peugeot, C., The Intuitive Experience, in The View
from Within. First-person approaches to the study of conscious-
ness, F.J.Varela and J. Shear, Editors. 199, Imprint Academic:
London,. p. 43-77.
263. Cutler, J.A., et al., An overview of randomized trials of sodium
reduction and blood pressure. Hypertension, 1991. 17(1
Suppl): p. I27-133.
264. MacMahon, S., et al., Obesity and hypertension: epidemiologi-
cal and clinical issues. Eur Heart J, 1987. 8 Suppl B: p. 57-70.
265. MacMahon, S., et al., Blood pressure, stroke, and coronary
heart disease. Part 1, Prolonged differences in blood pressure:
prospective observational studies corrected for the regression
dilution bias. Lancet, 1990. 335(8692): p. 765-774.
266. McCraty, R., et al., New Hope for Correctional Ofcers: An In-
novative Program for Reducing Stress and Health Risks. Appl
Psych and Biofeedback 2009. 34(4): p. 251-272.
267. Lehrer, P., et al., Biofeedback treatment for asthma. Chest,
2004. 126(2): p. 352-361.
268. Lehrer, P., Carr, RE., Smetankine, A., Vaschillo, E., Peper, E.,
Porges, S., Edelberg, R., Hamer, R., Hochron, S., Respiratory
sinus arrhythmia versus neck/trapezius EMG and incentive
inspirometry biofeedback for asthma: a pilot study. Applied
Psychophysiology & Biofeedback, 1997. 22(2): p. 95-109.
269. Lehrer, P.M., E. Vaschillo, and B. Vaschillo, Resonant frequency
biofeedback training to increase cardiac variability. Rationale
and manual for training. Applied Psychophyisology and
Biofeedack, 2000. 25(3): p. 177-191.
270. Karavidas, M., Psychophysiological Treatment for Patients with
Medically Unexplained Symptoms: A Randomized Controlled
Trial. Psychosomatics, in press.
271. Hassett, A.L., et al., A pilot study of the efcacy of heart rate
variability (HRV) biofeedback in patients with bromyalgia. Appl
Psychophysiol Biofeedback, 2007. 32(1): p. 1-10.
272. Karavidas, M.K., et al., Preliminary results of an open label
study of heart rate variability biofeedback for the treatment of
major depression. Appl Psychophysiol Biofeedback, 2007.
32(1): p. 19-30.
273. McCraty, R., M. Atkinson, and L. Lipsenthal, Emotional self-
regulation program enhances psychological health and quality
of life in patients with diabetes. Boulder Creek, CA: HeartMath
Research Center, HeartMath Institute, Publication No. 00-
006., 2000.
274. Bradley, R.T., McCraty, R., Atkinson, M., Tomasino., D., Emo-
tion Self-Regulation, Psychophysiological Coherence, and Test
Anxiety: Results from an Experiment Using Electrophysiologi-
cal Measures. Applied Psychophysiology and Biofeedback,
2010. 35(4): p. 261-283.
275. Luskin, F., et al., A controlled pilot study of stress manage-
ment training of elderly patients with congestive heart failure.
Preventive Cardiology, 2002. 5(4): p. 168-172, 176.
276. Arguelles, L., R. McCraty, and R.A. Rees, The heart in holistic
education. Encounter: Education for Meaning and Social
Justice, 2003. 16(3): p. 13-21.
277. Barrios-Choplin, B., R. McCraty, and B. Cryer, An inner qual-
ity approach to reducing stress and improving physical and
emotional wellbeing at work. Stress Medicine, 1997. 13(3):
p. 193-201.
278. McCraty, R., Heart-brain neurodynamics: The making of emo-
tions2003, Boulder Creek, CA: HeartMath Research Center,
HeartMath Institute, Publication No. 03-015.
279. McCraty, R. and M. Atkinson, Spontaneous heart rhythm
coherence in individuals practiced in positive-emotion-focused
techniques. Unpublished data, 1998.
280. McCraty, R., et al., Impact of the Power to Change Performance
program on stress and health risks in correctional ofcers2003:
Boulder Creek, CA: HeartMath Research Center, HeartMath
Institute, Report No. 03-014, November 2003.
109
© Copyright 2015 HeartMath Institute
281. Nada, P.J., Heart rate variability in the assessment and biofeed-
back training of common mental health problems in children.
Med Arh, 2009. 63(5): p. 244-8.
282. Bradford, E.J., K.A. Wesnes, and D. Brett, Effects of peak
performance training on cognitive function. Journal of Psy-
chopharmacology, 2005. 19(5 suppl): p. A44.
283. Kim, S., et al., Heart rate variability biofeedback, executive
functioning and chronic brain injury. Brain Inj, 2013. 27(2): p.
209-22.
284. Berry, M.E., et al., Non-pharmacological Intervention for Chronic
Pain in Veterans: A Pilot Study of Heart Rate Variability Biofeed-
back. Global Advances in Health and Medicne, 2014. 3(2):
p. 28-33.
285. Soer, R., et al., Heart Coherence Training Combined with Back
School in Patients with Chronic Non-specic Low Back Pain:
First Pragmatic Clinical Results. Appl Psychophysiol Biofeed-
back, 2014.
286. Scott, L.D., W.-T. Hwang, and A.E. Rogers, The impact of mul-
tiple care giving roles on fatigue, stress, and work performance
among hospital staff nurses. Journal of Nursing Administra-
tion, 2006. 36(2): p. 86-95.
287. Salmond, S. and P.E. Ropis, Job stress and general well-being:
a comparative study of medical-surgical and home care nurses.
Medsurg Nursing, 2005. 14(5): p. 301.
288. Pipe, T. and J. Bortz, Mindful leadership as healing practice:
Nurturing self to serve others. International Journal for Hu-
man Caring, 2009. 13(2): p. 34-38.
289. Sarabia-Cobo, C., Heart Coherence: A New Tool in the Man-
agement of Stress on Professionals and Family Caregivers
of Patients with Dementia. Applied Psychophysiology and
Biofeedback, 2015: p. 1-9.
290. Watson, J., Nursing: Human science and human care: A theory
of nursing1999: Jones & Bartlett Learning.
291. Lemaire, J.B., Wallllace J E, Lewin A M , de Grood J, Schaefer
J P, The effect of a biofeedback-based stress management tool
on physician stress: a randomized controlled clinical trial. Open
Medicine, 2011. 5(4): p. 154-163.
292. HeartMath, L.L.C., Return on Investment. White Paper, 2009.
293. Reissner, A., The dance of partnership: A theological reflection.
Missiology: An International Review, 2001. 29(1): p. 3-10.
294. Nahser, F. and S. Mehrtens, What’s Really Going On?1993,
Chicago: Corporantes.
295. Goldman, L., Breaking the Silence: A Guide to Helping Children
with Complicated Grief-Suicide, Homicide, AIDS, Violence and
Abuse2014: Routledge.
296. Perry, B.D., Childhood experience and the expression of genetic
potential: What childhood neglect tells us about nature and
nurture. Brain and mind, 2002. 3(1): p. 79-100.
297. Costello, E.J., et al., Psychiatric disorders in pediatric primary
care. Prevalence and risk factors [see comments]. Arch Gen
Psychiatry, 1988. 45(12): p. 1107-16.
298. Scales, P.C., Reducing risks and building developmental assets:
Essential actions for promoting adolescent health. Journal of
School Health, 1999. 69(3): p. 113-119.
299. Bennett, W., The Index of Leading Cultural Indicators: Facts
and Figures on the State of American Society1994, New York:
Simon & Schuster.
300. Resnick, M.D., L.J. HARRIS, and R.W. Blum, The impact of
caring and connectedness on adolescent health and well-being.
J Paediatr Child Health, 1993. 29(s1): p. S3-S9.
301. Bradley, R.T., et al., Reducing Test Anxiety and Improving Test
Performance in America’s Schools: Results from the TestEdge
National Demonstration Study2007, Boulder Creek, CA: Heart-
Math Research Center, HeartMath Institute, Publication No.
07-09-01.
302. Hartnett-Edwards, K. and T.C.G. University, The Social Psy-
chology and Physiology of Reading/language Arts Achievement
2006: Claremont Graduate University.
303. Connolly, F., Evaulation of a HeartMath / Safe Place Programme
with Sshool Childern in West Belfast, 2009, Greater Falls Extended
Schools: http://taketen.tv/le/fccBrochure.pdf. p. 1-12.
304. Bradley, R.T., et al., Efcacy of an Emotion Self-regulation
Program for Promoting Development in Preschool Children.
Glob Adv Health Med, 2012. 1(1): p. 36-50.
305. May, R.W., M.A. Sanchez-Gonzalez, and F.D. Fincham, School
burnout: increased sympathetic vasomotor tone and attenuated
ambulatory diurnal blood pressure variability in young adult
women. Stress, 2014(0): p. 1-9.
306. May, R.W., K.N. Bauer, and F.D. Fincham, School Burnout:
Diminished Academic and Cognitive Performance. Learning
and Individual Differences. . In review
307. Bajkó, Z., et al., Anxiety, depression and autonomic nervous
system dysfunction in hypertension. J Neurol Sci, 2012.
317(1): p. 112-116.
308. FitzGerald, L., et al., Effects of dipping and psychological traits
on morning surge in blood pressure in healthy people. Journal
of Human Hypertension, 2012. 26(4): p. 228-235.
309. Matthews, K.A., et al., Blood pressure reactivity to psychologi-
cal stress predicts hypertension in the CARDIA study. Circula-
tion, 2004. 110(1): p. 74-78.
310. Unsworth, N., et al., An automated version of the operation span
task. Behavior research methods, 2005. 37(3): p. 498-505.
311. Unsworth, N., et al., Complex working memory span tasks
and higher-order cognition: A latent-variable analysis of the
relationship between processing and storage. Memory, 2009.
17(6): p. 635-654.
Bibliography
110
© Copyright 2015 HeartMath Institute
Science of the Heart
312. Babraj, J.A., et al., Extremely short duration high intensity
interval training substantially improves insulin action in young
healthy males. BMC Endocrine Disorders, 2009. 9(1): p. 3.
313. Rakobowchuk, M., et al., Sprint interval and traditional endur-
ance training induce similar improvements in peripheral arte-
rial stiffness and flow-mediated dilation in healthy humans.
American Journal of Physiology-Regulatory, Integrative and
Comparative Physiology, 2008. 295(1): p. R236-R242.
314. Patchell, B., Coherent Learning: Creating High-level Perfor-
mance and Cultural Empathy From Student to Expert. Global
Advances in Health and Medicine, 2014. 3(Suppl 1): p.
BPA17.
315. Vislocky, M. and R. Leslie, Efcacy and Implementation of
HeartMath Instruction in College Readiness Program: Improving
Students’ Mathematics Performance and Learning 2005, Uni-
versity of Cincinnati – Clermont College, Batavia OH: http://
mathematics.clc.uc.edu/Vislocky/CPR%20Project.htm.
316. deBoer, R.W., J.M. Karemaker, and J. Strackee, Hemodynamic
fluctuations and baroreflex sensitivity in humans: A beat-to-beat
model. American Journal of Physiology, 1987. 253(3 Pt 2):
p. H680-H689.
317. Association, A.P., Stress in America: ndings2010.
318. Hoel, H., K. Sparks, and C.L. Cooper, The cost of violence/stress
at work and the benets of a violence/stress-free working environ-
ment. Geneva: International Labour Organization, 2001.
319. Kalia, M., Assessing the economic impact of stress [mdash]
The modern day hidden epidemic. Metabolism, 2002. 51(6):
p. 49-53.
320. Bliss, W.G., Cost of employee turnover. The Advisor, 2004.
321. Cooper, C. and R. Payne, eds. Causes, Coping and Conse-
quences of Stress at Work. 1988, John Wiley & Sons Ltd.:
New York.
322. Goetzel, R.Z., et al., The relationship between modifiable
health risks and health care expenditures. An analysis of the
multi-employer HERO health risk and cost database. The Health
Enhancement Research Organization (HERO) Research Commit-
tee. Journal of Occupational and Environmental Medicine,
1998. 40(10): p. 843-854.
323. Bosma, H., et al., Low job control and risk of coronary heart
disease in Whitehall II (prospective cohort) study. Bmj, 1997.
314(7080): p. 558-65.
324. Berkman, L.F. and S.L. Syme, Social networks, host resistance,
and mortality: a nine-year follow-up study of Alameda County
residents. Am J Epidemiol, 1979. 109(2): p. 186-204.
325. Hermes, G.L., et al., Social isolation dysregulates endocrine
and behavioral stress while increasing malignant burden of
spontaneous mammary tumors. Proc Natl Acad Sci U S A,
2009. 106(52): p. 22393-8.
326. Marmot, M.G. and S.L. Syme, Acculturation and coronary
heart disease in Japanese-Americans. Am J Epidemiol, 1976.
104(3): p. 225-47.
327. Neser, W., H. Tyroler, and J. Cassel, Social disorganization
and stroke mortality in the black population of North Carolina.
American Journal of Epidemiology, 1971. 93(3): p. 166-175.
328. Ornstein, R. and D. Sobel, The Healing Brain1987, New York:
Simon and Schuster.
329. Lynch, J.J., A Cry Unheard: New Insights into the Medical Con-
sequences of Loneliness2000, Baltimore, MD: Bancroft Press.
330. Uchino, B.N., J.T. Cacioppo, and J.K. Kiecolt-Glaser, The rela-
tionship between social support and physiological processes: a
review with emphasis on underlying mechanisms and implica-
tions for health. Psychol Bull, 1996. 119(3): p. 488-531.
331. Cohen, S. and S. Syme, eds. Social Support and Health. 1985,
Academic Press: Orlando.
332. Ornish, D., Love and Survival: The Scientic Basis for the Healing
Power of Intimacy1998, New York: HarperCollins Publishers.
333. Pipe, T.B., et al., Building personal and professional resources
of resilience and agility in the healthcare workplace. Stress
and Health, 2012. 28(1): p. 11-22.
334. Newsome, M., et al., Changing Job Satisfaction, Absenteeism,
and Healthcare Claims Costs In a Hospital Culture. Global Ad-
vances in Health and Medicine, 2014. 3(Suppl 1): p. BPA01.
335. Riley, K. and D. Gibbs, HeartMath in UK healthcare: Does it add
up? Journal of holistic healthcare, 2013. 10(1): p. 23-28.
336. Murphy, H., Caring Theory and HeartMath: A Match Made in
Heaven. Global Advances in Health and Medicine, 2014.
3(Suppl 1): p. BPA18.
337. Goldsher, A.M., B. Hounslow, and J. Blank, Transforming and
Sustaining the Care Environment. Global Advances in Health
and Medicine, 2014. 3(Suppl 1): p. BPA11.
338. Bosteder, L. and S. Hargrave, Learning within a Prison Envi-
ronment: Will Emotional Intelligence Training Benet Female
Inmates Participating in a Work-based Education Program?,
2008, Oregon State University: https://www.heartmath.org/
research/research-library/educational/learning-within-a-
prison-environment/. p. 1-3.
339. McCraty, R., A. Deyhle, and D. Childre, The global coherence
initiative: creating a coherent planetary standing wave. Glob
Adv Health Med, 2012. 1(1): p. 64-77.
340. Uyeda, S., et al., Geoelectric potential changes: possible precur-
sors to earthquakes in Japan. Proc Natl Acad Sci U S A, 2000.
97(9): p. 4561-6.
341. Kopytenko, Yu A., et al. “Detection of ultra-low-frequency emis-
sions connected with the Spitak earthquake and its aftershock
activity, based on geomagnetic pulsations data at Dusheti and
Vardzia observatories. Physics of the Earth and Planetary
Interiors 77.1(1993): p. 85-95
342. Cornelissen, G., et al., Chronomes, Time Structures, for Chro-
nobioengineering for “A Full Life”. Biomedical Instrumentation
and Technology, 1999. 33: p. 152-187.
111
© Copyright 2015 HeartMath Institute
343. Doronin, V.N., Parfentev, V.A., Tleulin, S.Zh, .Namvar, R.A.,
Somsikov, V.M., Drobzhev, V.I. and Chemeris, A.V., Effect of
variations of the geomagnetic eld and solar activity on human
physiological indicators. Biozika, 1998. 43(4): p. 647-653.
344. Kay, R.W., Geomagnetic Storms: Association with Incidence
of Depression as Measured by Hospital Admission. British
Journal of Psychiatry, 1994. 164: p. 403-409.
345. Mikulecký, M., Solar activity, revolutions and cultural prime in
the history of mankind. Neuroendocrinology Letters, 2007.
28(6): p. 749-756.
346. Burch, J.B., Reif, J.S., Yost, M.G. , Geomagnetic disturbances
are associated with reduced nocturnal excretion of a melatonin
metabolite in humans. Neuroscience Letters, 1999. 266: p.
209-212.
347. Rapoport, S.I., Blodypakova, T.D., Malinovskaia, N.K., Orae-
vskii, V.N., Meshcheriakova, S.A., Breus, T.K. and Sosnovskii,
A.M., , Magnetic storms as a stress factor. Biozika, 1998.
43(4): p. 632-639.
348. Pobachenko, S.V., Kolesnik, A. G., Borodin, A. S., Kalyuzhin,
V. V., The Contigency of Parameters of Human Encephalograms
and Schumann Resonance Electromagnetic Fields Revealed
in Monitoring Studies. Complex Systems Biophysics, 2006.
51(3): p. 480-483.
349. Persinger, M.A., Sudden unexpected death in epileptics follow-
ing sudden, intense, increases in geomagnetic activity: preva-
lence of effect and potential mechanisms. Int J Biometeorol,
1995. 38(4): p. 180-187.
350. Stoupel, E., Sudden cardiac deaths and ventricular extrasys-
toles on days of four levels of geomagnetic activity. J. Basic
Physiol. Pharmacol., 1993. 4(4): p. 357-366.
351. Belov, D.R., Kanunikov, I. E., and Kiselev, B. V., Dependence of
human EEG synchronization on the geomagnetic activity on the
day of experiment. Ross Fiziol. Zh Im I M Sechenova, 1998.
84(8): p. 761–774.
352. Villoresi, G., Ptitsyna, N.G., Tiasto, M.I. and Iucci, N., Myocar-
dial infarct and geomagnetic disturbances: analysis of data on
morbidity and mortality [In Russian]. Biozika, 1998. 43(4): p.
623-632.
353. Gordon, C., Berk, M. , The effect of geomagnetic storms on
suicide. South African Psychiat Rev, 2003. 6: p. 24-27.
354. Kay, R.W., Schizophrenia and season of birth: relationship to
geomagnetic storms. Schiz Res, 2004. 66: p. 7-20.
355. Malin, S.R.C.a.S., B.J., Correlation between heart attacks and
magnetic activity. Nature, 1979. 277: p. 646-648.
356. Nikolaev, Y.S., Rudakov, Y.Y., Mansurov, S.M. and Mansurova,
L.G., Interplanetary magnetic eld sector structure and distur-
bances of the central nervous system activity. Reprint N 17a,
Acad. Sci USSR, IZMIRAN, Moscow, 1976: p. 29.
357. Oraevskii, V.N., Breus, T.K., Baevskii, R.M., Rapoport, S.I.,
Petrov, V.M., Barsukova, Zh.V., Gurnkel’ IuI, and Rogoza,
A.T. , Effect of geomagnetic activity on the functional status
of the body. Biozika, 1998. 43(5): p. 819-826.
358. Zaitseva, S.A.a.P., M. I., Effect of solar and geomagnetic activity
on population dynamics among residents of Russia [In Russian].
Biozika, 1995. 40(4): p. 861-864.
359. Persinger, M.A., Wars and increased solar-geomagnetic activity:
aggression or change in intraspecies dominance? Percept Mot
Skills, 1999. 88(3 Pt 2): p. 1351-1355.
360. Kleimenova, N. and O. Kozyreva, Daytime quasiperiodic
geomagnetic pulsations during the recovery phase of the
strong magnetic storm of May 15, 2005. Geomagnetism and
Aeronomy, 2007. 47(5): p. 580-587.
361. Subrahmanyam, S., P. Narayan, and T. Srinivasan, Effect of
magnetic micropulsations on the biological systems — A bioen-
vironmental study. International Journal of Biometeorology,
1985. 29(3): p. 293-305.
362. Halberg, F., et al., Cycles Tipping the Scale between Death and
Survival (=”Life”). Progress of Theoretical Physics Supple-
ment 2008. 173: p. 153-181.
363. Otsuka, K., et al., Chronomics and “Glocal” (Combined Global
and Local) Assessment of Human Life. Progress of Theoretical
Physics Supplement, 2008. 173: p. 134-152.
364. Persinger, M.A., Geopsychology and geopsychopathology:
Mental processes and disorders associated with geochemical
and geophysical factors. Experientia, 1987. 43: p. 92-104.
365. Dimitrova, S., Stoilova, I. and Cholakov, I., Influence of Local
Geomagnetic Storms on Arterial Blood Pressure. Bioelectro-
magnetics, 2004. 25: p. 408-414.
366. Hamer, J.R., Biological entrainment of the human brain by low
frequency radiation. Northrop Space Labs, 1965: p. 65-199.
367. Rapoport, S.I., Malinovskaia, N.K., Oraevskii, V.N., Komarov,
F.I., Nosovskii, A.M. and Vetterberg, L., , Effects of distur-
bances of natural magnetic eld of the Earth on melatonin
production in patients with coronary heart disease. Klin Med
(Mosk), 1997. 75(6): p. 24-26.
368. Ertel, S., Space weather and revolutions: Chizhevsky’s helio-
biological claim scrutinized. Studia Psychologica, 1996. 39:
p. 3-22.
369. Grigoryev, P., Rozanov, V., Vaiserman, A., Vladimirskiy, B.,
Heliogeophysical factors as possible triggers of suicide ter-
roristic acts. Health, 2009. 1(4): p. 294-297.
370. Smelyakov, S.V. Tchijevsky’s Disclosure: How the Solar Cycles
Modulate the History. http://www.ASTROTHEOS.COM 2006.
371. Tchijevsky, A.L., (de Smitt, V.P. translation), Physical Factors
of the Historical Process. Cycles, 1971. 22: p. 11-27.
372. Ertel, S., Cosmophysical correlations of creative activity in
cultural history. Biophysics, 1998. 43(4): p. 696-702.
373. Stoupel, E., et al., Ambulatory blood pressure monitoring in pa-
tients with hypertension on days of high and low geomagnetic
activity. J Hum Hypertens, 1995. 9(4): p. 293-4.
Bibliography
112
© Copyright 2015 HeartMath Institute
Science of the Heart
374. Anshel, M.H., Effect of age, sex, and type of feedback on mo-
tor performance and locus of control. Res Q, 1979. 50(3): p.
305-17.
375. Cornelissen, G., et al. Gender differences in circadian and
extra-circadian aspects of heart rate variability (HRV). in 1st
International Workshop of The TsimTsoum Institute. 2010.
Krakow, Poland.
376. Oinuma, S., et al., Graded response of heart rate variability,
associated with an alteration of geomagnetic activity in a
subarctic area. Biomed Pharmacother, 2002. 56(Suppl 2):
p. 284s-288s..
377. Anshel, M.H. and D. Marisi, Effect of music and rhythm on
physical performance. Res Q, 1978. 49(2): p. 109-13.
378. McCraty, R., The energetic heart: Bioelectromagnetic com-
munication within and between people, in Bioelectromagnetic
Medicine, P.J. Rosch and M.S. Markov, Editors. 2004, Marcel
Dekker: New York. p. 541-562.
379. Kemper, K.J. and H.A. Shaltout, Non-verbal communication
of compassion: measuring psychophysiological effects. BMC
Complement Altern Med, 2011. 11: p. 132..
380. Montagnier, L., et al., Transduction of DNA information
through water and electromagnetic waves. arXiv preprint
arXiv:1501.01620, 2014.
381. Persinger, M., On the possible representation of the electro-
magnetic equivalents of all human memory within the earth’s
magnetic led: Implications of theoretical biology. Theoretical
Biology Insights, 2008. 1: p. 3-11.
382. Persinger, M.A., On the possibility of directly accessing every
human brain by electromagnetic induction of the fundamental
alogorithms Perceptual and Motor Skills, 1995. 80: p. 791-
799.
383. Davies, J.L., Alleviating political violence through enhancing
coherence in collective consciousness: Impact assessment
analysis of the Lebanon war. Dissertation Abstracts Interna-
tional, 1988. 49(8): p. 2381A.
384. Hagelin, J., The Power of the Collective. Shift: At the Frontier
of Consciousness, 2007. 15: p. 16-20.
385. Hagelin, J.S., Orme-Johnson, D. W., Rainforth, M., Cavanaugh,
K., & Alexander, C. N. , Results of the National Demonstration
Project to Reduce Violent Crime and Improve Governmental
Effectiveness in Washington, D.C. Social Indicators Research,
1999. 47: p. 153-201.
386. Orme-Johnson, D.W., et al., International Peace Project in the
Middle East THE EFFECTS OF THE MAHARISHI TECHNOLOGY
OF THE UNIFIED FIELD The Journal of Conict Resolution,
1988. 32(4): p. 776-812.
387. Bancel, P., Nelson, R., The GCP Event Experiment: Design,
Analytical Methods, Results. Journal of Scientic Exploration,
2008. 22(3): p. 309-333.
388. Nelson, R., Effects of Globally Shared Attention and Emotion.
Journal of Cosmology, 2011. 14.
389. Wendt, H.W., Mass emotions apparently affect nominally
random quantum processes: interplanetary magnetic eld
polarity found critical, but how is causal path?, 2002, Halberg
Chronobiology Center, University of Minnesota: St. Paul.
390. Ameling, A., Prayer: an ancient healing practice becomes new
again. Holist Nurs Pract, 2000. 14(3): p. 40-8.
391. Gillum, F. and D.M. Grith, Prayer and spiritual practices for
health reasons among American adults: the role of race and
ethnicity. J Relig Health. 49(3): p. 283-95.
392. Schwartz, S.A. and L. Dossey, Nonlocality, intention, and
observer effects in healing studies: laying a foundation for the
future. Explore (NY). 6(5): p. 295-307.
1985-1511
USA $19.95
14700 West Park Avenue, Boulder Creek, California 95006
831-338-8500 • www.heartmath.org
... According to McCraty (2015), intuition can be categorized into three distinct forms. Implicit knowledge, energy sensitivity, and nonlocal intuition. ...
... Perhaps for this reason, in many definitions and explanations, intuition is treated as a more or less implicit reading of signs as a result of the senses and experience. As mentioned by McCraty (2015), it may be a frequency, a biological energy or electricity sensing mechanism that are generally associated with telepathy and foresight whose center may be the brain, heart or gut, as a potential power, gift or ability of our nature of creation or of the evolution process that we have not yet been able to name, that we have not experienced concretely until today, that we have not yet realized its existence. If considered from this perspective, it is thought that it is necessary to first study whether it is, rather than what it is. ...
... It is believed that when we connect deeply with our hearts and are in tune with our emotions, our intuition becomes clearer and more accessible. This alignment allows us to make decisions, make connections, and navigate life in a more authentic and meaningful way (McCraty, 2015;Salem, 2009). McCraty et al. (2004a) study, 30 calm and 15 emotionally arousing images were shown to 26 individuals in two experimental conditions: a baseline condition representing normal psychophysiological functioning and a condition promoting physiological consistency. ...
Article
Full-text available
Intuition is generally taken as a belief, experience, and tool for knowledge emergence, often characterized by emotional judgments, sensations or foresight and be classified into various types. Recently researchers have started to search for somatic markers for intuition using EEG and ECG. The objective of this study is to explore the correlations between measurements that serve as indicators of heart rate variability and the strength and kind of intuition based on samples self-reports. The samples are 149 students aged 19-21 at Kocaeli University. Data was collected using KYTO2935 HRV sensors, Elite HRV Bluetooth application and the Intuitive Thinking Scale. Research findings indicate correlations between intuitive thinking skills and certain sub-dimensions and specific heart rhythm indices. These correlations vary in terms of their effect sizes, but it is satisfactory to assert that certain features of ours, which are acknowledged as intuitive thinking abilities, are connected to heart rhythm indices and require more thorough investigations.
... Skills that enhance heart rate variability (HRV) are a promising direction, as higher HRV contributes to the healthy functioning of self-regulatory capability and psychophysiological resilience (McCraty, 2022;McCraty et al., 2006). HRV is a measure of the variance in time intervals between each heartbeat (McCraty, 2015(McCraty, , 2022. ...
... HeartMath practices regulate emotional experience (subjectively and physiologically) and produce an emotionally, mentally, and physiologically balanced or coherent state (McCraty, 2015). McCraty (2022) recently reviewed a large body of research demonstrating the connections between self-induced positive emotions, stronger HRV patterns, greater psychophysiological coherence, and enhanced psychosocial well-being. ...
... This coherence can be "measured by heart rate variability (HRV) analysis, wherein a person's heart rhythm pattern becomes more ordered" (McCraty, 2015, p. 26). Research has illustrated that emotions impact heart-brain communication, which can be measured by HRV (McCraty, 2015(McCraty, , 2022. ...
Article
Full-text available
It is important to address social and emotional concerns early on, as they can adversely affect learning at all levels. The classroom is an ideal context for fostering healthy social and emotional development. For example, emotion regulation can be reinforced through simple daily practices within schools. The current applied research project was in collaboration with multiple community partners and assessed the effectiveness of a classroom‐based HeartMath practice (Heart Lock‐In) on resting heart rate variability (HRV) and self‐reported emotional benefits in elementary students. This repeated‐measures study was conducted in central Alberta, Canada, in 2020 and involved obtaining pre–post HRV measurements from N = 24 grade five students who participated in a teacher‐led 5‐min Heart Lock‐In (like loving‐kindness—radiating love to oneself and others) daily for 4 weeks. We hypothesized that the practice would increase resting HRV compared to a 4‐week relaxation control. Qualitative questions were included to capture perceptions of the utility and impact of the practice. Univariate analysis of variance revealed that the HeartMath intervention significantly increased HRV compared to the relaxation control. Students reported enhanced emotional stability, feeling more positive about themselves, and improved interpersonal relationships. They expressed that the practice gives them better focus, which helps us to improve their performance (e.g., in academics and athletics). These findings provide evidence that a simple and short HeartMath ER practice can be practical for school educators, administrators, and counselors to implement in the classroom.
... The heart generates by far the strongest EMF in the body, surpassing the brain's output in both electric and magnetic strength. As the predominant source of EMF oscillations, the heart produces nonlinear interactions affecting the entire complex system's behavior of a human being (McCraty, 2016). The heart may act as a predominant node in the body's physiological EMF network (Schubert, 1993;Becker and Selden, 1985). ...
Article
Full-text available
All cells in the human body, including cancer cells, possess specific electrical properties crucial for their functions. These properties are notably different between normal and cancerous cells. Cancer cells are characterized by autonomous oscillations and damped electromagnetic field (EMF) activation. Cancer reduces physiological variability, implying a systemic disconnection that desynchronizes bodily systems and their inherent random processes. The dynamics of heart rate, in this context, could reflect global physiological network instability in the sense of entrainment. Using a medical device that employs an active closed-loop system, such as administering specifically modulated EMF frequencies at targeted intervals and at low energies, we can evaluate the periodic oscillations of the heart. This procedure serves as a closed-loop control mechanism leading to a temporary alteration in plasma membrane ionic flow and the heart’s periodic oscillation dynamics. The understanding of this phenomenon is supported by computer simulations of a mathematical model, which are validated by experimental data. Heart dynamics can be quantified using difference logistic equations, and it correlates with improved overall survival rates in cancer patients.
... Additionally, the index of coherence (IC = [LF/ HF − 1.75]/[LF/HF + 1.75]) is usually calculated and considered an immediate index of the state of sympathovagal balance. One of the software that provides the representation of IC to customers is the Inner Balance application (HeartMath, LLC;McCraty, 2016). This program shows the IC as a percentage of time in either high, medium, or low coherence. ...
Article
Full-text available
Stress is a psychophysical condition that causes an impairment in athletes' performance by causing an increase in sympathetic activity and an autonomic imbalance. The current methods for the measurement of psychophysiological stress introduce the use of the heart rate variability as a useful index of the well-being of these people. The heart rate variability corresponds to the time intervals between consecutive heartbeats, such as an irregularity in the normal sinus heart rhythm whose variability is due to the control exercised by a complex system of mechanisms, including the respiratory control system, and provides information about the activity of the sympathetic and parasympathetic branches of the autonomic nervous system. This review aims at summarizing the promising results, despite small amount, of the recent literature on the efficacy of heart rate variability biofeedback on the autonomic imbalance and psychophysical well-being of athletes as well as cognitive and motor performance.
Article
Full-text available
The aging population in Canada has been increasing continuously throughout the past decades. Amongst this demographic, around 11% suffer from some form of cognitive decline. While diagnosis through traditional means (i.e., Magnetic Resonance Imagings (MRIs), positron emission tomography (PET) scans, cognitive assessments, etc.) has been successful at detecting this decline, there remains unexplored measures of cognitive health that could reduce stress and cost for the elderly population, including approaches for early detection and preventive methods. Such efforts could additionally contribute to reducing the pressure and stress on the Canadian healthcare system, as well as improve the quality of life of the elderly population. Previous evidence has demonstrated emotional facial expressions being altered in individuals with various cognitive conditions such as dementias, mild cognitive impairment, and geriatric depression. This review highlights the commonalities among these cognitive health conditions, and research behind the contactless assessment methods to monitor the health and cognitive well-being of the elderly population through emotion expression. The contactless detection approach covered by this review includes automated facial expression analysis (AFEA), electroencephalogram (EEG) technologies and heart rate variability (HRV). In conclusion, a discussion of the potentials of the existing technologies and future direction of a novel assessment design through fusion of AFEA, EEG and HRV measures to increase detection of cognitive decline in a contactless and remote manner will be presented.
Article
Full-text available
The field of organ transplantation, particularly heart transplantation, has brought to light interesting phenomena challenging traditional understandings of memory, identity, and consciousness. Studies indicate that heart transplant recipients may exhibit preferences, emotions, and memories resembling those of the donors, suggesting a form of memory storage within the transplanted organ. Mechanisms proposed for this memory transfer include cellular memory, epigenetic modifications, and energetic interactions. Moreover, the heart's intricate neural network, often referred to as the "heart brain," communicates bidirectionally with the brain and other organs, supporting the concept of heart-brain connection and its role in memory and personality. Additionally, observations from hemispherectomy procedures highlight the brain's remarkable plasticity and functional preservation beyond expectations, further underscoring the complex interplay between the brain, body, and identity. However, ethical and philosophical questions regarding the implications of these findings, including the definition of death and the nature of personal identity, remain unresolved. Further interdisciplinary research is needed to unravel the intricacies of memory transfer, neuroplasticity, and organ integration, offering insights into both organ transplantation and broader aspects of neuroscience and human identity. Understanding these complexities holds promise for enhancing patient care in organ transplantation and deepens our understanding of fundamental aspects of human experience and existence.
Article
Full-text available
When the eye uses the brain and heart, the cardiovascular and nervous systems integrate and interact. Because changes in retinal microcirculation are independent predictors of cardiovascular events, the eye serves as a "display" to the cardiovascular system and brain. The eye, which has two circulatory systems and a rich vascular supply, is a prime candidate for this study and benefits from early damage to the target organ. Eye movements performed during the visual search pose a challenge in identifying critical points in the eye scene. Because it uses different brain pathways and relates to the cardiac cycle, humans’ ability to spot anomalies under challenging circumstances means they are always needed for visual search. ECG (electrocardiogram), electroencephalogram (EEG), and eye tracking can improve visual search training and attention-tracking performance. EEG data can also be analyzed in real time using eye-tracking technology. Previous work has discussed the EEG or ECG concerning attraction during visual search. The eyeball’s movement combined with the ECG in the previous investigation and introduced large electroencephalographic (EEG) artifacts. This assessment aims to (a) identify brain–heart coherent features influenced by the visual search task and (b) discover the behavior of EEG frequency bands and heart rate variability (HRV) features. EEG and ECG were used to analyze and predict inattention in individuals during a visual search task. The EEG determines human brain function and considers to detect the variability in the EEG frequency band. The work proposed a visual search task with EEG and ECG analysis. Five participants recorded EEG and ECG recordings in three different scenarios: rest, gaze tracking, and normal. Statistical evaluation was used to compare EEG and ECG characteristics and Pearson’s correlation was employed for statistical analysis. Statistical ANOVA analysis revealed statistically significant (p > 0.05) differences between theta (F3) and alpha (F3) EEG and ECG features, as well as between theta (F4) and alpha (F4) EEG and ECG features. Additionally, alpha (F3) and theta (F3) were significant in the heart rate variability index (rMSSD), which monitored activity under eye tracking. There was also a significant difference between alpha (F3) and mean HR. Pearson’s correlation between ECG and EEG shows that theta (O1) and alpha (O1) correlate with LF/HF and alpha (F3) and theta (F3) with rMSSD. Theta (F3) and mean heart rate were also correlated. Observing the above ECG and EEG characteristics can improve and control treatment options for conditions like neurovascular instability (NCVI), characterized by age-related changes in blood pressure and increased cerebral and cardiac leukoaraiosis.
Article
Full-text available
The review article "Harmonizing Hearts and Habitats: The Symbiosis of Brahma Kumaris Raja Yoga Meditation and Environmental Consciousness" delves into the profound relationship between Brahma Kumaris Raja Yoga Meditation and environmental awareness. In the context of pressing environmental challenges, the article emphasizes the intertwining of human consciousness and the natural world. It explores how Raja Yoga Meditation, rooted in ancient Indian spiritual wisdom, serves as a bridge between inner growth and environmental consciousness. By fostering self-awareness, mindfulness, and spiritual development, this practice enables a holistic understanding of one's role in the environment and encourages a shift from consumerism to sustainability. The article examines how Raja Yoga Meditation empowers collective efforts to reshape the relationship between individuals, society, and nature. It highlights the interdisciplinary scope of the topic, spanning spirituality, psychology, philosophy, and environmental studies. Through analysis of literature, case studies, and practitioner experiences, the article uncovers the intricate connections between spiritual enlightenment and environmental stewardship. Ultimately, the review urges readers to recognize the ecological implications of personal journeys towards self-realization. In a time of urgent environmental challenges, it emphasizes the impact of inner transformation on the planet's well-being. The article advocates for a harmonious alliance between spirituality and responsible environmental stewardship, offering hope for a more balanced coexistence between humans and the natural world.
Article
Full-text available
The purpose of this study is to investigate the effects of 10-week heart rate variability biofeedback training on basketball skills, free throws, and heart rate variability parameters. Twenty-four basketball players (experimental, n = 12 and control, n = 12) aged 18–24 years volunteered to participate in this study. The experimental group participated in a 10-week heart rate variability biofeedback and basketball training program, while the control group only participated in the 10-week basketball training session. Basketball free-throw performance, basketball skills, and heart rate variability tests were conducted on the experimental and control groups before and after the 10-week intervention. Consequently, we discovered that basketball free-throw performance, breathing frequency, and heart rate variability parameters, which reflect vagal modulation of parasympathetic activity, improved in participants who underwent the 10-week heart rate variability biofeedback and basketball training, and not in those who took basketball training only. Our findings propose that heart rate variability biofeedback, alongside basketball workouts, can contribute to better basketball free-throw performance potentially through improved autonomic nervous system functioning. Keywords Basketball performance · Heart rate variability · Basketball free-throw · Biofeedback
Article
Full-text available
Extrapolating from B. L. Fredrickson's (1998, 2001) broaden-and-build theory of positive emotions, the authors hypothesized that positive emotions are active ingredients within trait resilience. U.S. college students (18 men and 28 women) were tested in early 2001 and again in the weeks following the September 11th terrorist attacks. Mediational analyses showed that positive emotions experienced in the wake of the attacks - gratitude, interest, love, and so forth - fully accounted for the relations between (a) precrisis resilience and later development of depressive symptoms and (b) precrisis resilience and postcrisis growth in psychological resources. Findings suggest that positive emotions in the aftermath of crises buffer resilient people against depression and fuel thriving, consistent with the broaden-and-build theory. Discussion touches on implications for coping.
Article
Full-text available
Handwritten autobiographies from 180 Catholic nuns, composed when participants were a mean age of 22 years, were scored for emotional content and related to survival during ages 75 to 95. A strong inverse association was found between positive emotional content in these writings and risk of mortality in late life (p < .001). As the quartile ranking of positive emotion in early life increased, there was a stepwise decrease in risk of mortality resulting in a 2.5-fold difference between the lowest and highest quartiles. Positive emotional content in early-life autobiographies was strongly associated with longevity 6 decades later. Underlying mechanisms of balanced emotional states are discussed.
Article
Social support has consistently been shown to be beneficial for both physiological and psychological health; however the benefits of social support vary greatly depending on how it is defined and measured. Having social ties is consistently linked to lower mortality and better mental health, but specific instances of support are often associated with negative outcomes. This consistent finding is a well‐known paradox in the social support literature: individuals benefit from knowing that support is available but often suffer when it is received. We discuss several theories that attempt to explain the association between social support and multiple health‐related outcomes.
Article
Leaders benefit from focusing on self-nurturing behaviors and ways of being in order to have sustained energy to care for others. Leaders have a large role in caring for each other and modeling courage for self-care. The science of caring (Watson, 2008) guides exploration of the importance of self-nurture for leaders. Caritas-based leadership practices of lovingkindness/equanimity toward self and cultivating one’s own spiritual practices frame this discussion. Mindfulness is presented in the context of leadership practice. An applied example of research involving mindfulness-based stress reduction in nursing leaders is included. Practical resources for incorporating self-nurturing behaviors are provided.
Article
Kopytenko, Yu.A., Matiashvili, T.G., Voronov, P.M., Kopytenko, E.A. and Molchanov, O.A., 1993. Detection of ultra-low-frequency emissions connected with the Spitak earthquake and its aftershock activity, based on geomagnetic pulsations data at Dusheti and Vardzia observatories. Phys. Earth Planet. Inter., 77: 85—95. ULF electromagnetic emissions from the Spitak (Armenia) earthquake site have been detected. Observations were carried out at the Dusheti and Vardzia (Georgia) observatories at distances 120—200 km from the epicentre in a frequency range 0.005—1 Hz. It is shown that the emission appears several hours before the main shock and some of the powerful aftershocks and is not connected with geomagnetic pulsations of magnetospheric sources.