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Official Publication of the Academy of Family Physicians of India
Volume 8 / Issue 12 / December 2019
www.jfmpc.com
ISSN 2249-4863
Journal of
Family Medicine
and Primary Care
Journal of Family Medicine and Primary Care • Volume 8 • Issue 12 • December 2019 • Pages ***-***
Spine 13 mm
© 2019 Journal of Family Medicine and Primary Care | Published by Wolters Kluwer - Medknow 3915
Introduction
Sleep is a normal and essential human behaviour. However, many
research studies show abnormal sleep patterns or sleep disorders
among older subjects and sleep workers.[1] Sleep disorders may result
in fatigue, tiredness, depression and problems in daytime functioning.
In patients of cardiovascular disorders (CVDs), respiratory disorders
and metabolic disorders, chronic sleep disorders are common.[2,3]
It has been found from population‑based studies that
approximately 30% of the adult samples drawn from different
countries report one or more of the symptoms of insomnia like
difculty initiating sleep, difculty maintaining sleep, waking up
too early or non‑restorative or poor quality of sleep.[4]
Pharmacological treatment to overcome sleep disorders are used
widely, but their use is limited by side effects and long‑term
intervention.[5] As sleep is affected by both physiological and
psychological factors, many researchers tried to explore effect of
mind–body intervention like music on sleep.[1] Music has been
found to decrease sympathetic nervous system activity; reduce
anxiety, blood pressure (BP), heart and respiratory rate and has
Effect of music of specic frequency upon the sleep
architecture and electroencephalographic pattern of
individuals with delayed sleep latency: A daytime nap
study
Pramita Dubey1, Yogesh Kumar1, Ramji Singh1, Kamlesh Jha1, Rajesh Kumar1
1Department of Physiology, AIIMS Patna, Bihar, India
Abs tr Ac t
Introduction: Sleep is normal human behaviour. However, the stress in daily life leads to altered sleep behaviour like insomnia,
parasomnia, etc. Owing to possible side effects, mind–body interventions like music, yoga and meditation could be a better
alternative intervention to pharmacological interventions for the condition. It is known that 432 Hz music to have some effect on the
overall sleep quality though some knowledge gap does exist. The present study aims to find the effects of 432 Hz on sleep quality
and sleep latency in a daytime nap among subjects with history of delayed sleep latency. Material and Method: Fifteen healthy
male volunteers aged 18 to 40 years with history of delayed sleep latency were recruited for the study from a cohort of working
staff and students at the institute, after due ethical clearance following the inclusion and exclusion criteria. All the subjects were
subjected to sleep study with and without music intervention at the gap of 1 week. Sleep parameters recorded include sleep
stages, electroencephalogram (EEG), electrocardiogram (ECG), electromyography (EMG), nasal airflow, thoracic movement, nasal
saturation etc. Result: Outcome of the study shows some decrease in the mean sleep latency (P > 0.05) with significant increase
in the energy of alpha waves (P < 0.01) at the sleep onset. Conclusion: It was concluded that 432 Hz music has some significant
calming effect as reflected by increased alpha activities without any significant effect upon the sleep latency in the daytime naps.
Keywords: 432 Hz music, Alpha energy, daytime nap, sleep latency
Original Article
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Website:
www.jfmpc.com
DOI:
10.4103/jfmpc.jfmpc_575_19
Address for correspondence: Dr. Kamlesh Jha,
Associate Professor, Department of Physiology, AIIMS,
Patna ‑ 801 507, Bihar, India.
E‑mail: drkamleshjha@gmail.com
How to cite this article: Dubey P, Kumar Y, Singh R, Jha K, Kumar R.
Eect of music of specic frequency upon the sleep architecture and
electroencephalographic pattern of individuals with delayed sleep latency:
A daytime nap study. J Family Med Prim Care 2019;8:3915-9.
This is an open access journal, and articles are distributed under the terms of the Creative
Commons Attribution‑NonCommercial‑ShareAlike 4.0 License, which allows others to
remix, tweak, and build upon the work non‑commercially, as long as appropriate credit is
given and the new creations are licensed under the identical terms.
For reprints contact: reprints@medknow.com
Received: 23‑07‑2019 Revised: 20‑08‑2019
Accepted: 21‑10‑2019 Published: 10‑12‑2019
Dubey, et al.: Effect of music on daytime sleep architecture
Journal of Family Medicine and Primary Care 3916 Volume 8 : Issue 12 : December 2019
positive effects on sleep via muscle relaxation and distraction
from thoughts. Music has been a part of meditation since ancient
times. Certain records mention use of 432 Hz music as very
benecial tone for inducing sleep. Musicians describe it by words
like correct and peaceful tone. However, no previous study in my
knowledge has proven effect of 432 Hz music on sleep pattern.
Mind–body interventions use a variety of techniques designed
to increase the mind’s capacity to affect bodily function and
symptoms. These include meditation, prayer, mental healing and
therapies that use creative outlets, such as art, music or dance.[6]
Few studies have focused on the effects of music, as a
non‑pharmacological method of improving the quality of sleep
in older adults. A study (Lai et al., 2005) investigated the effects
of soft music on sleep quality in older community in Taiwan.
It found the use of soothing music as an empirically based
intervention for sleep in older people.[7]
Harmat et al. (2008) investigated the effects of music on sleep
quality in young participants with poor sleep. It states that
sleep disorders may result in fatigue, tiredness, depression and
problems in daytime functioning.[8] Hernández (2005) explored
the effect of a music therapy procedure (music listening paired
with progressive muscle relaxation [PMR]) on the reduction of
anxiety and improvement of sleep patterns in abused women in
shelters. It indicated that music therapy constituted an effective
method for reducing anxiety levels and improving sleep quality.[9]
A study by Choi (2010) examined the effects of music and PMR
on anxiety, fatigue, and improvement of quality of life (QoL)
in family caregivers.[10]
Music therapy is a method, which takes the advantage of
therapeutic inuence of music on psychological and somatic
sphere of the human body. It has a modifying inuence on
vegetative, circulatory, respiratory and endocrine systems.
Music show reduced psychopathologic symptoms (anxiety
and depression), improves self‑rating, influences quality
and disorders of sleep, reduces pain and improves patients’
openness, readiness and co‑operation in treatment process.
Music therapy is a conventional treatment and makes up part of
an integral whole together with physiotherapy, kinesiotherapy
and recuperation.[11]
Aim and Objectives
This study aims to study the effect of 432 Hz music on sleep
pattern and sleep latency in the subjects with increased sleep
latency. Objectives are to nd association between 432 Hz music
and different sleep study parameters like Sleep stages, EEG, ECG,
EMG, nasal airow, thoracic movement and oxygen saturation.
Hypothesis
Playing 432 Hz music for 15 to 20 min before sleeping induces
sleep and increases deep sleep phase (Stage 3 and 4).
Material and Methods
The study was conducted in sleep lab in department of
physiology of All India Institute of Medical Sciences (AIIMS),
Patna after taking ethical clearance from the institutional ethics
committee. Twenty‑ve apparently normal healthy male subjects,
aged 18 to 40 years were recruited for the study initially after
written informed consent but only 15 subjects could complete the
study successfully. Subjects were seen to be spending maximum
time in non‑REM (NREM) sleep. Most of the subjects achieved
N2 stage of sleep, both with music and without music. Many did
not achieve REM stage and deep sleep. Therefore, the subjects
achieving N2 stage in both studies (polysomnography with
music and polysomnography without music) were included in
the study and others were excluded. Subjects included in the
study were male volunteers from AIIMS, Patna campus, aged
group 18 to 40 years Male. Patients with history of sleep disorders
like hypersomnia, parasomnia, narcolepsy, obstructive sleep
apnoea, rapid eye movement (REM) sleep behaviour disorders,
circadian rhythm sleep disorders, periodic limb movement
disorders, shift work sleep disorders, etc., were excluded from the
study. Participants were instructed to abstain from any food or
beverage that contained caffeine 24 h prior to the study. A brief
demographic and medical history has been taken followed by
general physical examination before performance of the nap
study.
Nap study, using 58 Ch. polysomnograph SOMNOscreen™
EEG plus (Somnomedics, Germany) was performed during
afternoon time for minimum of 1:30 h to study the effect on
sleep. All the subjects have been scheduled for nap studies with
and without the intervention of music at a 1‑week interval.
Participants were instructed to come with clean hair, without oil
or conditioner. They were explained all the details of procedure.
The scalp was cleaned with alcohol scrub and an EEG 10–20 jelly
have been used to adhere electrodes. An impedance of about 1
Kohm have been obtained for each electrode. Polysomnographic
data have been recorded with a wireless sensor and analysed
using equipment specic software Domino (SOMNOscreen
ltd, Germany).
After connecting electrodes, music was played at a volume,
which was reported, comfortable and acceptable by the subject.
Recording of sleep parameters was started as subject went
to bed and lights were switched off. Total of minimum 1:30
hrs recording was taken. Subjects were allowed to awaken
spontaneously.
EEG data from O1, O2, P3, P4, F3, F4, A1, A2, EOG1, EOG2,
ECG data at two leads, chin movement, plethysmography,
periodic leg movements, chest and abdomen movements,
ECG, and nasal airow were used for analysis purpose. The
system acquired the data at a sampling frequency of 256 Hz
with bandpass lter applied at 0.3 Hz to 48 Hz and notch lter
of 50 Hz.
Dubey, et al.: Effect of music on daytime sleep architecture
Journal of Family Medicine and Primary Care 3917 Volume 8 : Issue 12 : December 2019
Data preprocessing
High‑frequency interferences were ltered out from EEG signals
by using a band‑pass lter with a range of 0.3 to 48 Hz. Then,
artefacts were removed by the blind‑source analysis algorithm
independent component analysis (ICA). Each subject’s signal
was decomposed into independent components (ICs). Then,
artefacts were selected and removed.
Feature extraction
In this study, EEG signals were segmented into 2‑min segments.
To ensure that all EEG data had the same length, 2 min segment
of second sleep stage was analysed. Features extracted were
energy, entropy, and power spectral density.
The energy of a signal depends upon the magnitude of the signal.
Wavelet packet node energy is more robust in representing a
signal. Total signal energy can be dened in equation (1).
EC
ij
j
N
==
∑||
2
1 (1)
Where, i = 1,2……l is the wavelet decomposition level from
level 1 to level l. N is the number of the coefcients of detail or
approximates at each decomposition level. To analyse specic
frequency region, suitable tree structure should be chosen, which
represent the wavelet packet energy distribution in that tree.
The data obtained from the subjects were evaluated using the
Statistical Package for Social Sciences (SPSS) software for the
data processing. Paired t‑test was applied to see if there was
any statistically signicant difference between energy of EEG
samples from recording with music and without music.
The energy was also compared without averaging, and individual
electrodes comparison was done. A more statistically signicant
difference was obtained in the right frontal and central region
between recording with music and recording without music.
Result
The demographic prole of the 15 participants is shown in
Table 1. The mean age of participants were 20.4 + 4.1, whereas
the mean body mass index (BMI) range was 23.2 ± 2.8. For the
convenience of the study, male participants were exclusively
taken for the study, as stated earlier.
In Table 2, sleep latency for different stages is compared.
Near to signicant difference is observed in latency of Stage 1
when comparing recording with music with recording without
music. (P = 0.10). Other stage latencies and percentage of
different stages during sleep do not show any statistically
signicant differences.
Table 3 compares the energy of alpha range frequency between
recording with music and recording without music. Statistically
signicant differences are obtained with a P = 1.17 × 10‑6.
The difference is best seen in energy of alpha frequencies
in the right frontal and central region, which is highly
signicant (P = 1.6 × 10‑5, P = 2.6 × 10‑5).
Similarly, the effect was seen in beta and alpha frequencies in the
right frontal and temporal regions.
Figure 1 shows the mean sleep latency among the subjects
with and without music induction. They showed a distinct
difference, though statistically not signicant at 95% condence
interval (CI) (P > 0.05). Figure 2 shows the alpha power among
subjects of both the groups with statistically signicant increase
in the subjects of music group in comparison to non‑music
group.
Discussion
Music has long been known to have some effect on the
psychophysical parameters of human beings. The present study
attempted to study the effect of a particular frequency of music,
i.e., 432 Hz music upon the sleep parameters of individuals
having subjective complaint of delayed sleep latency. The
parameters mainly studied included sleep latency, sleep latency
for individual sleep stages of NREM and REM sleep. Being
a daytime nap study, the sleep architecture did not follow the
classical pattern, usually observed during night‑time, and many
subjects could not achieve N3 or N4 stage. Besides sleep latency,
total sleep dime (TST), its ratio with various sleep stages and
power of alpha waves during N2 stage have been studied in
both groups.
It has been observed that sleep latency has shown some
observable decrease among the music group individuals in
Table 1: Demographic data of subjects (
n
=15)
Parameters Mean and SD
Age 20.46±4.20
Height 172.85±5
Weight 69.61±9.90
BMI 23.27±2.84
SD=Standard deviation, BMI=Body mass index
Figure 1: Sleep latency with and without music
Dubey, et al.: Effect of music on daytime sleep architecture
Journal of Family Medicine and Primary Care 3918 Volume 8 : Issue 12 : December 2019
comparison to the non‑music group participants though
statistically non‑signicant at 95% condence limit. REM latency
also showed a similar trend. Other parameters had mixed results
in both groups.
The most signicant observation of the study is the increase
in the alpha power during sleep seen among the study group
participants in comparison to the non‑music group observations,
which appears to be highly signicant statistically (P < 0.01).
Music therapy is a method, which takes the advantage of
therapeutic inuence of music on psychological and somatic
sphere of the human body. Its therapeutic properties are
increasing being used. Current scientic research has proved its
modifying inuence on vegetative, circulatory, respiratory and
endocrine systems. Works devoted to the effects of music on
the patients’ psychological sphere have also been conrmed.[11]
Normal sleep is characterised by behavioural and physiologic
changes, as well as cycling between two distinct sleep states, REM
and NREM. Throughout the sleep time, people cycle between
NREM and REM sleep via an ultradian rhythm, with most of
sleep spent in NREM.[12] In our study, subjects were seen to be
spending maximum time in NREM sleep. Most of the subjects
achieved N2 stage of sleep, both with music and without music.
Many did not achieve REM stage and deep sleep. Therefore, the
subjects achieving N2 stage in both studies (polysomnography
with music and polysomnography without music) were included
in the study and others were excluded.
Determinants involved in the regulation of sleep are the
homeostatic and circadian processes. Despite being highly
regulated, sleep is fragile, and its stages and duration may be
affected by multiple factors, such as age, drugs, temperature, and
medical and psychiatric disease. Our hypothesis is that music is
also thought to be a regulator of sleep stages and brain wave
activity.[12]
The observations indicate that though latency has some inuence of
music over it, The most promising effect of music upon the sleep
behaviour could possibly be the calming effect as represented by
the alpha dominance during Stage 2 of the NREM sleep. Alpha, as
is commonly known, represents the relaxed state of mind, and its
dominance among the music intervention group is indicative of the
possible calming or relaxing effect of 432 Hz music on the sleeping
brain. The alpha rhythm is typically seen in at least three different
types, which are different in topography and function. First, the
posterior alpha rhythm, originating from the parieto‑occipital
cortex, is dependent on the alertness and attentional factors. Second,
there is the mu rhythm, which is dominant in central electrodes and
Table 2: Sleep prole of subjects with and without music
Sr. No. Sleep Parameters Mean value and SD (with music) Mean value and SD (without music)
P
Latency (Min) 9.86±9.26 19.96±23.33 0.19
Latency N1 10±9.34 26.13±27.11 0.10
Latency N2 21.01±10.50 11.69±10.83 0.93
Latency Deep Sleep 25.49±7.32 23.47±9.26 0.44
Latency REM 25.69±20.88 31±34.63 0.18
REM TST% 19.49±20.16 33.08±20.05 0.28
N1 TST% 22.7±16.21 26.64±30.97 0.68
N2 TST% 40.91±21.86 31.03±12.50 0.16
N3 TST% 7.51±5.24 7.51±6.95 0.39
N4 TST% 33.26±24.71 38.65±20.55 0.74
SD=Standard deviation, REM=Rapid eye movement, TST=Total sleep time
Figure 2: Mean of alpha energy with music and mean of alpha energy
without music
Table 3: The energy for alpha frequency with and
without music for different participants
Subject Energy with music Energy without music
1 24.73 1.08
2 40.20 14.85
3 15.91 8.48
4 21.82 2.09
5 14.65 7.21
6 26.71 10.83
7 29.11 5.827
8 9.29 3.826
9 8.89 2.23
10 26.35 3.69
11 22.58 5.39
12 9.45 1.56
13 28.88 6.89
14 11.80 1.77
15 15.99 2.65
Dubey, et al.: Effect of music on daytime sleep architecture
Journal of Family Medicine and Primary Care 3919 Volume 8 : Issue 12 : December 2019
is related to the somatosensory cortex and movement. Third, the
tau rhythm originates from the auditory cortex. It is important to
stress that alpha power and brain activity are inversely related. This
means that roughly speaking, the bigger the alpha power, the less
active the brain. The alpha rhythm is typically predominant in the
awake‑resting state, either relaxed and comfortable (desynchronised
tonic slow alpha) or concentrated (phasic desynchronised alpha),
as well as in the case of alpha coma.[13]
Similarly, energy must also be inversely related to activity of
brain. Bigger the energy value, less active must be the brain, as
shown in this study, where energy is high with music and low
without music.
Conclusion
Music, especially the 432 Hz frequency has shown some
promising effect over the electroencephalographic activities of
brain during a daytime nap. The decrease in latency, although
not statistically signicant and statistically signicant increase in
energy of alpha frequency indicates that 432 music Hz frequency
music has some signicant relaxing effect on the sleeping brain
and equivocal effect upon the sleep latency, especially among the
individuals with delayed sleep latency.
Limitations
It was a unique study in which an apparently Nobel concept
of effect of music on sleep pattern and sleep latency has been
studied by a daytime nap study. However, due to resource‑limited
settings, it had some limitations. Instead of full night gold
standard polysomnographic recordings, which would have been
a better study technique to test the hypothesis, a daytime nap
study has been planned. Subjects were exclusively males, which is
another limitation of the study that authors would like to declare.
A further study with a bigger database in the light of above
ndings may be expected to be of high yield for scientic world.
Acknowledgement
Department of Physiology, AIIMS Patna.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conicts of interest.
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