R E S E A R C H Open Access
Effect of respiratory pattern on automated
clinical blood pressure measurement: an
observational study with normotensive
, Nnenna Harmony Nzeribe Nwobodo
, Ying Wang
, Fei Chen
and Dingchang Zheng
Background: It has been reported that deep breathing could reduce blood pressures (BP) in general. It is also
known that BP is decreased during inhalation and increased during exhalation. Therefore, the measured BPs could
be potentially different during deep breathing with different lengths of inhalation and exhalation. This study aimed
to quantitatively investigate the effect of different respiratory patterns on BPs.
Methods: Forty healthy subjects (20 males and 20 females, aged from 18 to 60 years) were recruited. Systolic and
diastolic BPs (SBP and DBP) were measured using a clinically validated automated BP device. There were two repeated
measurement sessions for each subject. Within each session, eight BP measurements were performed, including 4
measurements during deep breathing with different respiratory patterns (Pattern 1: 4.5 s vs 4.5 s; Patter 2: 6 s vs 2 s;
Pattern 3: 2 s vs 6 s; and Pattern 4: 1.5 s vs 1.5 s, respectively for the durations of inhalation and exhalation) and
additional 4 measurements from 1 min after the four different respiratory patterns. At the beginning and end of the
two repeated measurement sessions, there were two baseline BP measurements under resting condition.
Results: The key experimental results showed that overall automated SBP significantly decreased by 3.7 ± 5.7 mmHg,
3.9 ± 5.2 mmHg, 1.7 ± 5.9 mmHg and 3.3 ± 5.3 mmHg during deep breathing, respectively for Patterns 1, 2, 3 and 4
(all p< 0.001 except p< 0.05 for Pattern 3). Similarly, the automated DBPs during deep breathing in pattern 1, 2 and 4
decreased by 3.7 ± 5.0 mmHg, 3.7 ± 4.9 mmHg and 4.6 ± 3.9 mmHg respectively (all p< 0.001, except in Pattern 3 with
a decrease of 1.0 ± 4.3 mmHg, p= 0.14). Correspondingly, after deep breathing, automated BPs recovered back to
normal with no significant difference in comparison with baseline BP (all p> 0.05, except for SBP in Pattern 4).
Conclusions: In summary, this study has quantitatively demonstrated that the measured automated BPs decreased by
different amounts with all the four deep breathing patterns, which recovered back quickly after these single short-term
interventions, providing evidence of short-term BP decrease with deep breathing and that BP measurements should be
performed under normal breathing condition.
Keywords: Blood pressure, Breathing pattern, Diastolic, Exhalation, Fast-deep breathing, Inhalation, Respiratory pattern,
Slow-deep breathing, Systolic
* Correspondence: firstname.lastname@example.org
Health and Wellbeing Academy, Faculty of Medical Science, Anglia Ruskin
University, Chelmsford, UK
Full list of author information is available at the end of the article
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Herakova et al. Clinical Hypertension (2017) 23:15
The importance of accurate blood pressure (BP) meas-
urement is without doubt. According to a major review
in the Journal of the American Medical Association
(JAMA), a 5 mmHg error would result in 21 million
Americans being denied treatment or 27 million being
exposed to unnecessary treatment, depending on the dir-
ection of the error . Unfortunately, BP measurement
is still one of the most poorly performed diagnostic
measurements in real clinical practice . It is gener-
ally accepted that BP measurement inaccuracies are as-
sociated with the measurement conditions, including
incorrect patient posture, incorrect arm position and
incorrect cuff position and size [3–5], and also associ-
ated with short-term physiological changes during the
measurement leading to within-subject BP variability
. It has been widely accepted that respiration is one
of the key factors affecting short-term physiological
changes in BP and therefore leading to potential meas-
urement error .
Respiration is the natural physiological mechanism
during which air is inhaled into the lungs and then ex-
haled via the nose or mouth. Normal breathing is invol-
untary and rhythmic, and two processes are involved
during breathing are inspiration (or inhalation) and ex-
piration (or exhalation) [7, 8]. During inspiration with
oxygen inhaled into the body, the intercostal muscles
contract, expanding the ribcage and the diaphragm con-
tracts, pulling down to increase the volume of the chest.
This lowers the pressure inside the thorax and gets air
sucked into the lungs. During exhalation with carbon di-
oxide exhaled out of the body, the intercostal muscles
relax and lower the ribs downward, causing the diaphragm
to relax and move back upwards. This causes a decrease
in thorax volume, which as a result, increases the pressure
inside the thorax.
Several published studies have shown that respiration
influences both short-term and long-term systolic and
diastolic blood pressures (SBP and DBP) measured by
different techniques [6, 9–14]. For instance, it has been
reported by Zheng et al.  that, with regular slow and
deep breathing, both manual auscultatory SBP and DBP
decreased significantly by 4.4 and 4.8 mmHg respect-
ively, in comparison with normal breathing. On the
other hand, the physiological mechanisms of respiration
process indicate that BP is decreased during inhalation
and increased during exhalation . Since a single BP
measurement may take more than one or two normal
respiratory cycles, the measured BPs could be potentially
different with different types of deep breathings where
various lengths of inhalation and exhalation are involved.
To the best of our knowledge, there is little quantitative
information available on the effect of different respira-
tory patterns on measured BPs.
The aim of this research was to quantitatively investi-
gate the effect of different breathing patterns on BPs in
comparison with baseline BP measurement.
Forty healthy normotensive subjects, 20 males and 20 fe-
males, aged 18–60, were recruited. The requirements of
inclusion criteria included: normal healthy individual,
age range 18–60 years old, with SBP < 140 mmHg and
DBP < 90 mmHg. Participants with known hypertension
and antihypertensive medical treatment, or cardiovascu-
lar disease, such as ischaemic heart disease, congestive
heart failure, chronic atrial fibrillation, renal failure and
previous stroke, were excluded. Additionally, if the initial
BP measurement showed SBP > 140 mmHg and DBP >
90 mmHg, these participants were also excluded. Subjects’
demographic information, including age, weight, height
and arm circumference are summarized in Table 1.
This study has been reviewed and approved by the
Faculty Research Ethics Panel, Faculty of Medical Sci-
ence, Anglia Ruskin University. The investigation con-
formed with the Declaration of Helsinki, and all subjects
gave their written informed consent to participate in the
Blood pressure measurement protocol and procedure
The measurements were conducted in a quiet room at
Anglia Ruskin University. All the subjects were asked to
rest in a seated position for at least 5 min before the for-
mal BP measurement. SBP, DBP were measured from
the left arm using a suitable cuff matched to individual
arm circumference (adult 24–34 cm; large adult 34–41 cm)
by a clinically validated automated BP device (HBPM
Omron, M6 Comfort). The HR value was also obtained
during each measurement from the device. The BP meas-
urement procedure followed the Measurement Guideline
from the European Society of Hypertension .
A mobile phone application (Paced Breathing, Android
App on Google Play), which was designed to adjust the
duration of inhalation and exhalation and display the
visual pattern on the screen (see Fig. 1b), was used for
the subjects to follow the different respiratory patterns
and synchronize their breathing with the defined patterns.
All subjects were given the opportunity to practice and be
Table 1 Demographic data of subjects studied
Subject information Minimum Maximum Mean Standard
Age 20 59 37 10
Height (cm) 151 183 170 9
Weight (kg) 51 108 74 14
Arm circumference (cm) 24 40 31 4
Herakova et al. Clinical Hypertension (2017) 23:15 Page 2 of 7
familiar with these respiratory patterns before the formal
There were two repeated measurement sessions for each
subject (see Fig. 1a). At the beginning and end of the two
sessions, there were two baseline BP and HR readings
under resting condition. Within each session, eight BP
and HR measurements were performed, including 4
measurements during deep breathing using four differ-
ent respiratory patterns and additional 4 measurements
from 1 min after the four different patterns of deep
breathing. During deep breathing with a certain re-
spiratory pattern, before the automated BP measure-
ment started, the subjects were asked to breathe three
respiratory cycles, and this continued until the BP
measurement completed. The order of the sequence of
the four respiratory patterns was randomised between
subjects. As shown in Fig. 1b), the details of the four
respiratory patterns were:
Pattern 1: slow deep breathing with 4.5 s of inhalation
and 4.5 s exhalation;
Pattern 2: long inspiration followed by short expiration
with 6 s inhalation and 2 s exhalation;
Pattern 3: short inspiration followed by long expiration
with 2 s inhalation and 6 s exhalation;
Pattern 4: fast deep breathing with 1.5 s inhalation and
1.5 s exhalation.
Data and statistical analysis
All recorded BP and HR data were stored in Excel
Spreadsheet, then transferred and analysed in statistical
software SPSS 20.0. The means and standard deviations
(SDs) of SBP, DBP and HR were calculated separately for
the baseline, during four different respiratory patterns,
and after deep breathings. Analysis of variance (ANOVA)
was then performed to investigate the measurement re-
peatability and the effect of respiratory pattern on BP and
HR measured during and after deep breathing. The post-
hoc multiple comparison in the ANOVA test was used to
compare the differences in BP and HR between respiratory
patterns. A pvalue below 0.05 was considered statistically
BP and HR measurement repeatability
ANOVA analysis showed that baseline BP and HR at the
beginning and end of the main measurement sessions
were repeatable (p=0.4for SBP,p=0.5 for DBPandp=0.6
for HR). Furthermore, BP and HR measurements during
and after deep breathing were also repeatable between the
repeat sessions (all p> 0.1). As the BP and HR measure-
ments were repeatable, their average values from the two
repeat measurements were used as a reference value for
HR changes during and after deep breathing in
comparison with baseline
Figure 2 shows the HRs measured during and after deep
breathing. In comparison with the Baseline, it can be
seen that HR during deep breathing increased signifi-
cantly in Patterns 3 and 4 (69.4 ± 9.3 and 70.1 ± 8.7 vs
67.1 ± 8.5 beats/min, both p< 0.01), but not in Patterns 1
and 2. After deep breathing, all the HRs recovered back
to normal with no statistically significant HR difference
in comparison with Baseline (all p> 0.2).
Fig. 1 aBP measurement procedure. Participants were given 5 min before the initial BP was measured. During deep breathing, before the automated
BP measurements started, 3 respiratory cycles were performed, and this continued until the completion of BP measurement. bIllustration of deep
breathing with four different respiratory patterns. Pattern 1: slow breathing (↑4.5 s ↓4.5 s); Pattern 2: long inspiration followed by short expiration
(↑6s↓2 s); Pattern 3: short inspiration followed by long expiration (↑2s↓6 s); Pattern 4: fast breathing (↑1.5 s ↓1.5 s)
Herakova et al. Clinical Hypertension (2017) 23:15 Page 3 of 7
SBP changes during and after deep breathing in
comparison with baseline
Figure 3a) shows SBP measured during and after deep
breathing. It can be seen that SBPs measured during
deep breathing were significantly decreased in compari-
son with the Baseline. Specifically, as shown in Fig. 4a)
and Table 2, SBP in Patterns 1, 2 and 4 decreased by
3.7 ± 5.7 mmHg, 3.9 ± 5.2 mmHg and 3.3 ± 5.3 mmHg
respectively (all p< 0.001) and SBP in Pattern 3 decreased
by 1.7 ± 5.9 mmHg (p< 0.05). It was also observed that
SBP after deep breathing did not change significantly in
comparison with Baseline in Pattern 1, 2, 3 (decreased by
1.0 ± 4.2 mmHg, 1.1 ± 3.5 mmHg, 1.2 ± 4.8 mmHg, with
DBP changes during and after deep breathing in
comparison with baseline
Figure 3b) shows DBP measured during and after deep
breathing. In comparison with the Baseline, DBP in
Patterns 1, 2 and 4 during deep breathing decreased
significantly by 3.7 ± 5.0 mmHg, 3.7 ± 4.9 mmHg and
4.6 ± 3.9 mmHg respectively (all p< 0.001). DBP in Pat-
tern 3 did not decrease significantly in comparison with
Baseline (mean difference of 1.0 ± 4.3 mmHg; p= 0.14).
DBP after deep breathing did not show significant
changes in comparison with Baseline (with the mean
decreased of −0.09 ± 4.15 mmHg, −0.14 ± 2.71 mmHg,
0.45 ± 2.71 mmHg and 0.46 ± 3.16 mmHg, respectively
Fig. 2 Means + SDs of HR measured during and after deep breathing, separately for different respiratory patterns.
comparison with baseline HR
Fig. 3 Means + SDs of systolic (a) and diastolic (b) blood pressures measured during and after deep breathing, separately for different respiratory
p<0.05 in comparison with baseline BP
Herakova et al. Clinical Hypertension (2017) 23:15 Page 4 of 7
Discussion and conclusions
This study quantitatively demonstrated the effect of dif-
ferent deep breathing patterns (with different durations
of inhalation and exhalation) on automated BPs. To the
best of our knowledge, this was the first study to com-
prehensively compare the short-term effect of different
breathing patterns on automated BPs.
According to the results of the present study, Pattern
1 (slow and deep breathing with 4.5 s inhalation and
4.5 s exhalation) achieved a significant decrease in both
automated SBP and DBP by 3.7 ± 5.7/3.7 ± 5.0 mmHg,
respectively. These results agreed with the findings from
previous studies, where it has been concluded that slow
and deep breathing could reduce BP [6, 10, 17, 18]. Some
of the published studies mainly focused on the long-term
effect, while the others on the short-term effect on BP
variability. Bhavanani, et al.  applied slow and deep
breathing with equal duration of inhalation and exhalation
at the rate of 6 breaths/min and achieved BP reduction in
hypertensive patients with 5 min of practice. With slow
deep breathing, BPs are reduced via increased baroreflex
sensitivity, which regulates BP by controlling heart rate,
sympathetic activity and chemoreflex activation . In
addition, any slight deviation in the oxygen content in the
brain may affect the cardiovascular function. During slow
and deep breathing, oxygenation allows the body to absorb
its full oxygen quota, which relaxes the brain and calms
the cardiovascular system, resulting in reduced stress and
This study also showed significant decrease in automated
SBP/DBP (3.9 ± 5.2 mmHg/3.7 ± 4.9 mmHg, respectively)
in Pattern 2 with 6 s inhalation and 2 s exhalation. This
Fig. 4 Decrease of systolic (a) and diastolic (b) blood pressures (SBP and DBP) during and after deep breathing in comparison with baseline. The
results for different respiratory patterns are given separately.
p< 0.05 in comparison with baseline BP
Table 2 Means ± SDs of systolic and diastolic blood pressures (SBP and DBP) measured during and after deep breathing and their
differences in comparison with baseline BPs
During breathing BP decrease After breathing BP decrease
Baseline 111.5 ± 10.5
Pattern 1 107.8 ± 11.5 3.7 ± 5.7
110.4 ± 10.7 1.0 ± 4.2
Pattern 2 107.6 ± 12.2 3.9 ± 5.2
110.3 ± 10.3 1.1 ± 3.5
Pattern 3 109.7 ± 13.0 1.7 ± 5.9
110.3 ± 12.2 1.2 ± 4.8
Pattern 4 108.2 ± 11.3 3.3 ± 5.3
109.5 ± 10.2 1.9 ± 3.5
Baseline 74.4 ± 8.2
Pattern 1 70.7 ± 9.0 3.7 ± 5.0
74.4 ± 9.0 −0.1 ± 4.1
Pattern 2 70.7 ± 8.0 3.7 ± 4.9
74.5 ± 8.6 −0.1 ± 3.3
Pattern 3 73.3 ± 9.2 1.0 ± 4.3 73.9 ± 8.8 0.5 ± 2.7
Pattern 4 69.7 ± 8.2 4.6 ± 3.9
73.9 ± 8.3 0.5 ± 3.2
Herakova et al. Clinical Hypertension (2017) 23:15 Page 5 of 7
could be explained by the temporary physiological effect of
decreasing stroke volume during long standing inhalation
or widened thoracic for downward movement of dia-
phragm . It is also noticed that there was no significant
HR change with this breathing pattern, indicating the po-
tential involvement of sympathetic de-activation and that
the BP lowering effect could be persistent during deep
The respiratory Pattern 3 involved 2 s inhalation and
6 s exhalation. Although some published studies used
similar pattern and achieved a positive BP reduction [10,
19, 21], the results of the present study showed that this
pattern only achieved significant automated SBP de-
crease (1.7 ± 5.9 mmHg), but for DBP (1.0 ± 4.3 mmHg).
This could be explained by the physiology of long exhal-
ation which relates to a relaxation of diaphragm and an
increase of intrathoracic pressure, refilling the left ven-
tricle with blood and causing BP to increase. Pattern 4
was the only patter where the fast breathing (1.5 s inhal-
ation and 1.5 s exhalation) was used. The HR was sig-
nificantly increased with this pattern. Although many
participants complained of light dizziness during the ex-
periment, significant decrease was still observed in SBP/
DBP (3.3 ± 5.3/4.6 ± 3.9 mmHg, respectively).
Overall, the four respiratory patterns applied in this
study all reduced the short-term BPs by different
amounts. It is noticed that the participants felt more
comfortable to follow some patterns than the others, in-
dicating different physiological mechanisms could be in-
volved in these patterns. There is also possibility of this
BP lowering effect might be from “self-notice”of own
respiration or concentration on own respiration regard-
less of respiratory pattern. Published report has showed
transcendental meditation is associated with reductions
of SBP and DBP . Similar BP reduction was observed
in both normotensive and hypertensive individuals. For a
better understanding of their underlying mechanisms,
more data about BP reduction efficacy of self-notice or
concentration on spontaneous respiration is required in
a future study.
In addition, this study also showed that the measured
BPs recovered back to normal 1 min after the deep
breathings, with no significant difference in comparison
with Baseline. The only exception was SBP in Pattern 4
(with mean difference of BP by 1.9 ± 3.5 mmHg), which
can be explained by the fact that it takes longer for the
cardiovascular circulation to be stabilised. The results
provided evidence that, although short-term BP variability
was produced during deep breathing, both BP and HR
could recover quickly back to normal, suggesting that it is
better to measure BP under resting condition with normal
breathing pattern to achieve reliable BP values.
One of the limitations in this study is the fact that it was
not established whether the participants should inhale/
exhale with mouth or nose [17, 20, 23]. A comparison of
the effect of using different breathing approaches on BPs
could be included in a future study. Next, only the short-
term effect of deep breathing on BPs was investigated. The
long-term benefit of each breathing pattern with regular
practice should be investigated, to confirm whether rou-
tinely performed sessions of breathing exercises may lead
to a sustained reduction in BP for exploring its potential
clinical application. Furthermore, this preliminary study
was conducted only on normotensive subjects. The neuro-
humoral balance could be de-ranged in patients with
hypertension. Therefore, it is not guaranteed whether
similar results of this research could be achieved with
hypertensive patients or patients with other diseases.
It should be also noted that the measured BPs in this
study were from a clinically validated automated BP de-
vice. The automated BP device used here is based on
oscillometric technique, where BPs are normally esti-
mated from the global envelope of the oscillometric
pulses recorded from the whole period of the measure-
ment that covers several respiratory cycles. Since the
measuring principle of manual auscultatory technique is
different with the oscillometric technique, the effect of
different respiratory patterns on manual auscultatory BPs
could be different, depending on which phase (inspiration
or expiration) the SBP and DBP determinations are made
. The potential different effects of deep breathing on
manual and automated BPs are worth further investiga-
tion. It would be also useful to investigate the beat-to-beat
BP changes in association with deep breathing with differ-
ent respiratory patterns.
In summary, this study has quantitatively demon-
strated that the measured automated BPs decreased by
different amounts with all the four deep breathing pat-
terns, which recovered back quickly after these single
short-term interventions, providing scientific evidence
of short-term BP decrease with deep breathing and that
BP measurements should be performed under normal
BP: Blood pressure; DBP: Diastolic blood pressure; SBP: Systolic blood
pressure; SD: Standard deviation
Availability of data and materials
Data is available in a database from the corresponding author on reasonable
DZ, NH and FC conceived the idea and contributed to study design. NH
conducted the literature searches. NH, HNN and YW evaluated the
methodological quality, interpreted the data and made the analysis, having
full access to all data in this study and taking responsibility for the integrity
Herakova et al. Clinical Hypertension (2017) 23:15 Page 6 of 7
and accuracy of the data analysis. DZ and FC reviewed and commented on
the article. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Consent for publication
Not applicable. No individual data in any form is disclosed.
Ethics approval and consent to participate
Ethical approval was obtained from the Faculty Research Ethics Panel,
Faculty of Medical Science, Anglia Ruskin University. The written and
informed consent was obtained from all participants before they were
eligible into the study.
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
Health and Wellbeing Academy, Faculty of Medical Science, Anglia Ruskin
University, Chelmsford, UK.
Department of Computer Engineering, faculty of
Engineering, Enugu State University of Science and Technology, Enugu,
Department of Electrical and Electronic Engineering, Southern
University of Science and Technology, Shenzhen, China.
Received: 8 December 2016 Accepted: 11 April 2017
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