|Year : 2020 | Volume
| Issue : 2 | Page : 160-167
|Changes in heart rate variability after yoga are dependent on heart rate variability at baseline and during yoga: a study showing autonomic normalization effect in yoga-naïve and experienced subjects
Toshikazu Shinba1, Tomoko Inoue2, Takemi Matsui3, Kazuo Keishin Kimura4, Masanari Itokawa5, Makoto Arai5
1 Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Science; Department of Psychiatry, Shizuoka Saiseikai General Hospital, Shizuoka, Japan; Healthcare Systems Engineering Laboratory, Graduate School of Systems Design, Tokyo Metropolitan University, Tokyo
2 Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Science, Shizuoka, Japan; 3Healthcare Systems Engineering Laboratory, Graduate School of Systems Design, Tokyo Metropolitan University, Tokyo; Japan Yoga Therapy Society, Yonago, Tottori, Japan
3 Healthcare Systems Engineering Laboratory, Graduate School of Systems Design, Tokyo Metropolitan University, Tokyo
4 Japan Yoga Therapy Society, Yonago, Tottori, Japan
5 Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Science, Shizuoka, Japan
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|Date of Submission||05-May-2019|
|Date of Decision||22-Oct-2019|
|Date of Acceptance||12-Dec-2019|
|Date of Web Publication||30-Apr-2020|
| Abstract|| |
Background: Yoga therapy is widely applied to the maintenance of health and to treatment of various illnesses. Previous researches indicate the involvement of autonomic control in its effects, although the general agreement has not been reached regarding the acute modulation of autonomic function. Aim: The present study aimed at revealing the acute effect of yoga on the autonomic activity using heart rate variability (HRV) measurement. Methods: Twenty-seven healthy controls participated in the present study. Fifteen of them (39.5 ± 8.5 years old) were naïve and 12 (45.1 ± 7.0 years old) were experienced in yoga. Yoga skills included breath awareness, two types of asana, and two types of pranayama. HRV was measured at the baseline, during yoga, and at the resting state after yoga. Results: In both yoga-naïve and experienced participants, the changes in low-frequency (LF) component of HRV and its ratio to high-frequency (HF) component (LF/HF) after yoga were found to be correlated negatively with the baseline data. The changes in LF after yoga were also correlated with LF during yoga. The changes in HF as well as the raw HRV data after yoga were not related to the baseline HRV or the HRV during yoga. Conclusion: The results indicate that yoga leads to an increase in LF when LF is low and leads to a decrease in LF when it is high at the baseline. This normalization of LF is dependent on the autonomic modulation during yoga and may underlie the clinical effectiveness of yoga therapy both in yoga-naïve and experienced subjects.
Keywords: Autonomic activity, heart rate variability, low-frequency component, normalization effect, yoga therapy
|How to cite this article:|
Shinba T, Inoue T, Matsui T, Kimura KK, Itokawa M, Arai M. Changes in heart rate variability after yoga are dependent on heart rate variability at baseline and during yoga: a study showing autonomic normalization effect in yoga-naïve and experienced subjects. Int J Yoga 2020;13:160-7
|How to cite this URL:|
Shinba T, Inoue T, Matsui T, Kimura KK, Itokawa M, Arai M. Changes in heart rate variability after yoga are dependent on heart rate variability at baseline and during yoga: a study showing autonomic normalization effect in yoga-naïve and experienced subjects. Int J Yoga [serial online] 2020 [cited 2021 Dec 5];13:160-7. Available from: https://www.ijoy.org.in/text.asp?2020/13/2/160/283661
| Introduction|| |
Yoga therapy is a behavioral practice based on the ancient Indian discipline, and now, is widely used over the world for maintaining health and treating illnesses. It employs various skills of traditional yoga, which have been utilized in treating psychosomatic and psychiatric disorders by objectively perceiving the physical signs of the subject and promoting the self-control ability.
The underlying biological mechanisms of yoga therapy have been studied to further advance its use, and the involvement of autonomic modulation is suggested., In addition to heart rate (HR) and blood pressure,, HR variability (HRV) has been frequently used as a physiological parameter to estimate the influence of yoga on autonomic activity.,,,
Among various methods to analyze HRV, frequency-domain power-spectrum analysis is commonly used and calculates the high-frequency (HF) variation corresponding to respiration-related parasympathetic activity and the low-frequency (LF) variation corresponding to blood pressure-related activity., Using these HRV variables, yoga practitioners were found to have an increased parasympathetic activity at rest.,
The effects of yoga therapy have also been studied by measuring the HRV changes after 1 to several months of practices. Eight weeks of hatha yoga led to an increased parasympathetic tone. The autonomic balance tilted toward parasympathetic predominance after a 1-month practice of yoga including asana, pranayama, and dhyana. It has been reviewed that yoga can affect cardiac autonomic regulation with vagal dominance.
On the other hand, some studies concluded that no changes in HRV were found after yoga.,, A meta-analysis also indicates no convincing evidence for the effectiveness of yoga in modulating HRV.
The effects of yoga therapy are also dependent on the skills that are employed in the yoga practice. HRV measurement during dhyana suggested a reduced sympathetic activity and/or increased vagal modulation but showed no conclusive changes during ekagrata and cancalata. A decrease of parasympathetic activity has also been shown following kapalabhati but no significant changes after Nadi Shuddhi.
Most of the effects of yoga therapy introduced above were analyzed after the yoga practices for more than a month.,,, HRV data are known to be affected by psychological and physical conditions. The data separated by more than a month could be influenced by differences in these conditions at the time of measurement. Considering these limitations of previous researches, recent studies examined the acute effect of yoga therapy by measuring HRV before and after yoga. Following long Sudarshan Kriya Yoga, Bhaskar et al. reported that LF decreased and HF increased. On the other hand, Telles et al. examined the acute effects of several yoga skills and reported an increase of LF and a decrease of HF, indicating reduced parasympathetic activity. The acute effects of yoga on HRV shown in previous reports were not consistent. The results may depend on the yoga techniques that the study employs.
Considering the complexed relation between yoga and autonomic function introduced above, it would be interesting not only to compare the data before and after yoga but also to examine the relation of these data to the data during yoga. Bhagat et al. have reported that HRV indices are significantly altered during yoga in relation to the respiratory rhythm. It the present study, we recorded HRV at the resting baseline state, during yoga, and at the resting state immediately after yoga and further analyzed the relationships among them.
| Methods|| |
Twenty-seven healthy controls participated in this study, who had no history of cardiac, neurological, and mental disorders. Fifteen of them were naïve in yoga (age: 39.5 ± 8.5 years, mean ± standard deviation (SD), range: 22–54 years, 11 males, and 4 females). Twelve were experienced in yoga (age: 45.1 ± 7.0 years, mean ± SD, range: 32–54 years, 12 females), and the mean length of yoga experience was 11.6 ± 8.1 years. Written informed consent was obtained from each of the participants before starting the measurement. The average age of yoga-naïve participants was not different from that of experienced participants' (t-test, P > 0.05). The discrepancy in the male-to-female ratio between the groups came from consecutive assignments.
The participants participated in one session of the yoga of about 20 min. They were seated on a chair during yoga. The protocol included breath awareness, asana, and pranayama. The details are found in the publication by Kimura [Figure 1].
|Figure 1: A sample data of heart rate (HR) and heart rate variability parameters (high-frequency HF, low-frequency LF, low-frequency/high-frequency LF/HF, and low-frequency + high-frequency LF+HF) in a participant during a yoga session with multiple skills. The details of yoga skills are found in the text. The data during the rest periods were recorded both before (pre) and after (post) yoga. During yoga, heart rate and heart rate variability parameters show fluctuations|
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In brief, during the breath awareness skill, the participant put hands on the chest or the abdomen to feel the respiratory movement.
Asana is the isometric yogic breathing skill, and two types were employed in the present study. In the first one (hand-to-hand, asana 1), the participant pressed the hands together, and in the second (hand-to-head, asana 2), the participant pressed a side of the head with one hand. The pressure was generated between the hands (asana 1) or between the hand and head (asana 2), without movement for several seconds accompanied by inspiration. Then, the pressure was released for several seconds accompanied by expiration. The participant was instructed to perform this pressure/release for six times. The length of each pressure/release performance was monitored by an experimenter and was confirmed to be longer than 7 s in the present study (<0.15 Hz). The vocalization of sound “a” accompanied the pressure/release.
Pranayama in the present study consisted of two kinds of breathing skill, bhramari pranayama (pranayama 1) and 1:2 breathing (pranayama 2). In bhramari pranayama, the participants took a breath out slowly, accompanying vocalization of sound “n.” In the 1:2 breathing, the ratio of inspiration and expiration was instructed to be 1:2. The total length of each cycle was longer than 7 s (<0.15 Hz). The participants conducted bhramari pranayama breathing nine times and 1:2 breathing five times.
Each yoga skill was followed by a rest period of about 30 s before the next started.
The experimental protocol was approved by the Institutional Review Board of the Tokyo Metropolitan Institute of Medical Science.
Heart rate variability measurement
HRV was measured with the same method as that used in our previous study. At least 5 min of adaptation period was introduced before the start of the yoga protocol. During the experiment, the participant was seated on a chair with electrocardiogram (ECG) electrodes attached to the chest. ECG was measured conventionally with a gain of 10,000 and a time constant of 0.1 s. The signals were sampled at the frequency of 200 Hz and were stored in a computer for off-line analysis (Bonaly Light, GMS, Tokyo, Japan). R–R interval trend data were obtained using R-peaks of ECG, and their fluctuation was analyzed using maximum entropy method (MemCalc, GMS, Tokyo, Japan). The maximum entropy method was selected for the power spectrum analysis because it has been successfully applied to trend data with a minimum duration of 30 s and is useful for studies incorporating measurements of multiple behavioral states. R–R intervals between the range of 273 and 1500 ms were used for the analysis to exclude paroxysmal heart beats. When a R–R interval was omitted, it was replaced by the average of the preceding and the following intervals. These R–R intervals were resampled at the mean HR. MemCalc calculated LF and HF components of the spectrum every 2 s by integrating the power at the corresponding frequency intervals (LF: 0.04–0.15 Hz and HF: 0.15–0.4 Hz) for the preceding 30 s period. R–R intervals were also converted to HR (/min).
Pharmacological studies have shown that HF reflects parasympathetic activity related to respiratory frequency. LF reflects baroreceptor activity controlling blood pressure under the normal respiratory frequency and is related to both sympathetic and parasympathetic activities. In the present study, respiration was monitored, and its frequency was confirmed to be within the range of 0.15–0.4 Hz at the baseline and at the resting state after yoga.,, However, in the slow-breathing states during yoga skills, asana, and pranayama, the respiratory frequency was below 0.15 Hz, and the parasympathetic activity corresponds to HRV in the range of LF. During slow breathing, LF reflects both parasympathetic and baroreceptor activities. In the present study, the differences between the HF and LF scores during yoga and those scores at the baseline (yoga-pre) were calculated to quantify the autonomic modulation during yoga. It should be noted that during asana and pranayama with slow breathing, respiration-related parasympathetic activation was included in LF.
HF, LF, the sum of LF and HF (LF + HF), LF/HF, and HR were averaged in the interval from 30 s to the end of each yoga skill to exclude any data at the beginning of each new period that may still reflect the previous condition [Table 1]. The average of the data during all yoga skills was also calculated. HRV parameters and HR were measured at the baseline resting state (pre: 1 min), during yoga, and at the resting state after yoga (post: 1 min).
|Table 1: The data in all the participants are presented as mean (standard deviation, SD) at the baseline resting state (pre), during breath awareness (awareness), during two types of asana (asana 1: handtohand, asana 2: handtohead), and during two types of pranayama (pranayana 1: bhramari and pranayama 2: 1:2 breathing), the averaged data during these five yoga skills (average), and the data at the resting state after yoga (post)|
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Manipulation of data and statistical analysis
The data in the yoga-naïve and experienced participants were analyzed separately to examine the effect of yoga experience. In addition to the raw HRV data, the ratio of the data at the resting state after yoga (post) to that at the baseline resting state (pre) was used to evaluate the change after yoga (post/pre). The differences between HRV parameters during yoga and those at the baseline (yoga-pre) were also calculated to quantify the autonomic modulation during yoga, as described in the previous paragraph.
The raw parameters before (pre) and after (post) yoga at the resting states were compared using the Wilcoxon's signed-rank test. The relations between the ratio of the data (post/pre) and the baseline data (pre), between the ratio of the data (post/pre) and the data during yoga, and between the data during yoga and the baseline data (pre) were examined using Spearman's correlation coefficients (Prism 5, GraphPad, San Diego, CA, USA).
| Results|| |
The effects of yoga on heart rate and heart rate variability parameters
[Figure 1] presents an example of the recorded data in one participant. HR and HRV parameters showed fluctuations in the course of yoga therapy, depending on the behavioral states. [Table 1] summarizes the scores of HRV parameters during yoga protocol.
The changes of HR and HRV parameters after yoga are shown in [Figure 2]. On comparing the raw data at the resting state after yoga (post) and that at the baseline resting state before yoga, no statistical differences were observed for all HRV parameters in the yoga-naïve and experienced participants [yoga-naïve: [Figure 2]a, upper row, yoga-experienced: [Figure 2]b, upper row, HR, HF, LF, LF/HF, and LF + HF, P > 0.05].
|Figure 2: (a and b) The data from naïve and experienced subjects, respectively. Upper row: Changes in heart rate (HR) and heart rate variability parameters (high-frequency HF, low-frequency LF, low-frequency/high-frequency LF/HF, and low-frequency + high-frequency LF+HF) at the resting state after yoga (post) in comparison with that of before yoga (pre). The data from the same participant are connected by a line. No statistically significant differences are observed between the data before and after yoga (Wilcoxon signed-rank test, P > 0.05). Lower row: The low-frequency and low-frequency/high-frequency scores at the resting state before yoga (pre) plotted against the changes in these scores after yoga (post/pre). For these two parameters, “post/pre” scores show a correlation with “pre” scores (Spearman's correlation coefficients, P < 0.05). When the scores are high before yoga (pre), they tend to decrease, and when low, they tend to increase after yoga, presenting “normalization effect”|
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Heart rate variability changes after yoga and the baseline data
Direct comparison of the raw data before and after yoga did not reveal significant effect as shown above. However, on viewing the LF and LF/HF data of both naïve and experienced participants in [Figure 2]a and [Figure 2]b, it was speculated that high baseline score tended to decrease and low baseline score tended to increase after yoga in both the groups. This relation was examined using the ratio of the data at the resting state after yoga to that of before yoga (post/pre) and the data before yoga (pre), and a significant correlation between “post/pre” and “pre” was noted for LF and LF/HF [post/pre vs. pre in [Figure 2]a and [Figure 2]b, lower rows]. The change in LF and LF/HF after yoga was negatively correlated with the baseline data both in the yoga-naïve (LF: R = −0.595, P = 0.019, LF/HF: R = −0.796, P = 0.0004), [Figure 2]a, lower row] and in the experienced participants (LF: R = −0.588, P = 0.035, LF/HF: R = −0.577, P = 0.039), [Figure 2]b, lower row]. No correlation was found for HR, HF, and LF + HF (P < 0.05).
Heart rate variability changes after yoga and heart rate variability parameters during yoga
The ratio of the data after yoga to that before yoga (post/pre) was also compared to autonomic modulation during yoga. The data in the resting state inserted between yoga skills were omitted from the analysis. The baseline data were subtracted from the HF and LF data during yoga (yoga-pre), and the difference was considered to reflect autonomic modulation during yoga. The average of the data during all yoga skills as well as those during each yoga skill was used for the calculation.
Averaged raw data of HF and LF during yoga showed no statistically significant correlation with the post/pre ratio/ of HRV data (P > 0.05). On the other hand, the averaged LF change (yoga-pre) during all yoga skills was significantly correlated with post/pre ratio/of LF in both yoga-naïve (r = 0.68, P = 0.005) and experienced (r = 0.60, P = 0.038) participants [Figure 3] but not with that of HF (P > 0.05). In the yoga-naïve participants, the LF change during all yoga skills was also correlated with the post/pre ratio of LF/HF [r = 0.56, P = 0.029, [Table 2]. The correlation coefficients for individual yoga skills as well as the average of the data during all yoga skills are presented in [Table 2]. The LF change during asana was related to the post/pre ratio of LF. In yoga-naïve participants, LF change during breath awareness showed a significant correlation. The averaged HF change during yoga was not related to the post/pre ratio of HRV data [P > 0.05, [Figure 3].
|Figure 3: Relation of the changes in low-frequency scores after yoga (low-frequency LF post/pre) with the changes in high-frequency (HF) and low-frequency (LF) scores during yoga (yoga-pre) in naïve and experienced participants. The averaged high-frequency and low-frequency scores during all yoga skills were used for the calculation. The changes in low-frequency score after yoga (post/pre) did not exhibit relation with high-frequency change during yoga but showed significant correlation with low-frequency changes during yoga (Spearman's correlation coefficients, P < 0.05)|
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|Table 2: Correlation coefficient r between LF change during yoga from baseline (yoga-pre) and post/pre ratio of HRV indices|
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Baseline heart rate variability parameters and heart rate variability parameters during yoga
The relation of baseline autonomic activity to that during yoga was assessed by comparing the HRV data at the initial resting state and that during yoga. The results are presented in [Table 3]. In the yoga-naïve participants, the baseline LF scores are related to the LF change during yoga. In the yoga-experienced participants, the baseline HF shows a significant correlation with the LF change during yoga. HF changes during yoga showed no relation to baseline HRV data (P > 0.05).
|Table 3: Correlation coefficient r between LF change during yoga from baseline (yoga-pre) and HRV indices atbaseline rest|
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| Discussion|| |
The present study examined the autonomic basis of yoga effectiveness by examining the acute effect of yoga on HRV. In contrast to the previous reports supporting the augmentation of parasympathetic activity reflected in increased HF after long-term yoga therapy, the present study showed no significant acute effect on HF when it compared the data before and immediately after yoga and suggests that parasympathetic activation is not the major biological change for the acute effect.
As the acute effect of yoga therapy, the present results clarified the normalization of autonomic activity reflected in LF. Yoga leads to an increase in LF when LF is low and leads to a decrease when it is high at the baseline. LF/HF behaved in a similar manner. HF did not show such changes. The present study suggests the acute effects of yoga on LF.
LF is pharmacologically related to both sympathetic and parasympathetic activities and is known to be related to blood pressure fluctuation called Mayer wave. HR increases when the systolic blood pressure decreases and decreases when the blood pressure increases. This change in HR by baroreceptor activity is reflected in LF and enables a constant supply of blood flow to the body structures.
It is expected that an adequate level of LF is required to maintain the blood flow suitable to the environmental situation. Either excessive or insufficient LF would lead to an inadequate supply of blood flow. The normalization of LF by yoga can lead to suitable control of blood flow in response to behavioral changes. This normalization effect of yoga on the circulatory system may extend to autonomic activity, in general, involving both sympathetic and parasympathetic activities. Optimization of the level of autonomic activity should be important in maintaining a healthy state on facing stress or coping with diseases.
In the present study, asana was related to normalization in both yoga-naïve and experienced participants. Breath awareness was found to be related to normalization only in yoga-naïve participants. Pranayama was not directly related in the present study, although the effect of the order was not ruled out. Future studies are necessary to clarify which components of yoga skills are effective.
The present study further revealed that this normalization effect is related to autonomic modulation during yoga. This finding is based on the relation between the changes in LF after yoga and the LF during yoga. The LF increment (yoga-pre) during yoga was considered to involve breathing-related parasympathetic activity because the respiration rate during yoga skills fell into the range below 0.15 Hz. The present study may suggest that yoga, by adjusting respiration-related parasympathetic activation during yoga skills, normalizes the autonomic balance. It is also possible to assume that blood pressure-related autonomic modulation is controlled by yoga.
This acute normalization of autonomic activity by yoga is not restricted to experienced practitioners but is common to yoga-naïve participants. It is suggested that normalization is brought about without repetitive training of yoga and could be expected from the beginning of yoga therapy. However, the relation between the autonomic activation during yoga and the baseline HF is only found in yoga-experienced participants, suggesting that baseline parasympathetic activation by yoga is produced after long-term practice of yoga.
Yoga is also reported to be effective in neuropsychiatric patients including depression and anxiety.,,, It would be interesting to extend the present protocol to psychiatric patients.
Future study with a larger sample size containing adequate numbers of male and female is necessary to scientifically verify the present findings, especially with respect to gender.
| Conclusion|| |
The present study examined the acute effect of yoga on autonomic activity using HRV measurement during yoga. In both yoga-naïve and experienced participants, yoga leads to an increase in LF when LF is low and leads to a decrease when it is high at the baseline in relation to autonomic modulation during yoga. This normalization effect on autonomic activity may underlie the clinical effectiveness of yoga therapy.
Financial support and sponsorship
Tomoko Inoue received a research grant from Japan Yoga Therapy Society.
Conflicts of interest
There are no conflicts of interest.
| References|| |
Kimura KK. Yoga Therapy Theory: Modern Methods Based on Traditional Teachings of Human Structure and Function. Japan: Yoga Niketan; 2016.
Tyagi A, Cohen M. Yoga and heart rate variability: A comprehensive review of the literature. Int J Yoga 2016;9:97-113.
] [Full text]
Sullivan MB, Erb M, Schmalzl L, Moonaz S, Noggle Taylor J, Porges SW. Yoga therapy and polyvagal theory: The convergence of traditional wisdom and contemporary neuroscience for self-regulation and resilience. Front Hum Neurosci 2018;12:67.
Pramanik T, Sharma HO, Mishra S, Mishra A, Prajapati R, Singh S. Immediate effect of slow pace bhastrika pranayama on blood pressure and heart rate. J Altern Complement Med 2009;15:293-5.
Telles S, Verma S, Sharma SK, Gupta RK, Balkrishna A. Alternate-nostril yoga breathing reduced blood pressure while increasing performance in a vigilance test. Med Sci Monit Basic Res 2017;23:392-8.
Mourya M, Mahajan AS, Singh NP, Jain AK. Effect of slow- and fast-breathing exercises on autonomic functions in patients with essential hypertension. J Altern Complement Med 2009;15:711-7.
Satyapriya M, Nagendra HR, Nagarathna R, Padmalatha V. Effect of integrated yoga on stress and heart rate variability in pregnant women. Int J Gynaecol Obstet 2009;104:218-22.
Patra S, Telles S. Heart rate variability during sleep following the practice of cyclic meditation and supine rest. Appl Psychophysiol Biofeedback 2010;35:135-40.
Pal A, Srivastava N, Narain VS, Agrawal GG, Rani M. Effect of yogic intervention on the autonomic nervous system in the patients with coronary artery disease: A randomized controlled trial. East Mediterr Health J 2013;19:452-8.
Heart rate variability: Standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation 1996;93:1043-65.
Goldstein DS, Bentho O, Park MY, Sharabi Y. Low-frequency power of heart rate variability is not a measure of cardiac sympathetic tone but may be a measure of modulation of cardiac autonomic outflows by baroreflexes. Exp Physiol 2011;96:1255-61.
Peter R, Sood S, Dhawan A. Spectral parameters of HRV in yoga practitioners, athletes and sedentary males. Indian J Physiol Pharmacol 2015;59:380-7.
Tyagi A, Cohen M, Reece J, Telles S, Jones L. Heart rate variability, flow, mood and mental stress during yoga practices in yoga practitioners, non-yoga practitioners and people with metabolic syndrome. Appl Psychophysiol Biofeedback 2016;41:381-93.
Papp ME, Lindfors P, Storck N, Wändell PE. Increased heart rate variability but no effect on blood pressure from 8 weeks of hatha yoga – A pilot study. BMC Res Notes 2013;6:59.
Vinay AV, Venkatesh D, Ambarish V. Impact of short-term practice of yoga on heart rate variability. Int J Yoga 2016;9:62-6.
] [Full text]
Bertisch SM, Hamner J, Taylor JA. Slow yogic breathing and long-term cardiac autonomic adaptations: A pilot study. J Altern Complement Med 2017;23:722-9.
Cheema BS, Houridis A, Busch L, Raschke-Cheema V, Melville GW, Marshall PW, et al
. Effect of an office worksite-based yoga program on heart rate variability: Outcomes of a randomized controlled trial. BMC Complement Altern Med 2013;13:82.
Chu IH, Lin YJ, Wu WL, Chang YK, Lin IM. Effects of yoga on heart rate variability and mood in women: A randomized controlled trial. J Altern Complement Med 2015;21:789-95.
Posadzki P, Kuzdzal A, Lee MS, Ernst E. Yoga for heart rate variability: A systematic review and meta-analysis of randomized clinical trials. Appl Psychophysiol Biofeedback 2015;40:239-49.
Telles S, Raghavendra BR, Naveen KV, Manjunath NK, Kumar S, Subramanya P. Changes in autonomic variables following two meditative states described in yoga texts. J Altern Complement Med 2013;19:35-42.
Raghuraj P, Ramakrishnan AG, Nagendra HR, Telles S. Effect of two selected yogic breathing techniques of heart rate variability. Indian J Physiol Pharmacol 1998;42:467-72.
Shinba T, Kariya N, Matsui Y, Ozawa N, Matsuda Y, Yamamoto K. Decrease in heart rate variability response to task is related to anxiety and depressiveness in normal subjects. Psychiatry Clin Neurosci 2008;62:603-9.
Bhaskar L, Kharya C, Deepak KK, Kochupillai V. Assessment of cardiac autonomic tone following long sudarshan kriya yoga in art of living practitioners. J Altern Complement Med 2017;23:705-12.
Telles S, Singh D, Naveen KV, Pailoor S, Singh N, Pathak S. P300 and heart rate variability recorded simultaneously in meditation. Clin EEG Neurosci 2019;50:161-71.
Nivethitha L, Mooventhan A, Manjunath NK. Effects of various pranayama on cardiovascular and autonomic variables. Anc Sci Life 2016;36:72-7.
Bhagat OL, Kharya C, Jaryal A, Deepak KK. Acute effects on cardiovascular oscillations during controlled slow yogic breathing. Indian J Med Res 2017;145:503-12.
] [Full text]
Shinba T. Major depressive disorder and generalized anxiety disorder show different autonomic dysregulations revealed by heart-rate variability analysis in first-onset drug-naïve patients without comorbidity. Psychiatry Clin Neurosci 2017;71:135-45.
Kanaya N, Hirata N, Kurosawa S, Nakayama M, Namiki A. Differential effects of propofol and sevoflurane on heart rate variability. Anesthesiology 2003;98:34-40.
Sawada Y, Ohtomo N, Tanaka Y, Tanaka G, Yamakoshi K, Terachi S, et al
. New technique for time series analysis combining the maximum entropy method and non-linear least squares method: Its value in heart rate variability analysis. Med Biol Eng Comput 1997;35:318-22.
Akselrod S, Gordon D, Madwed JB, Snidman NC, Shannon DC, Cohen RJ. Hemodynamic regulation: Investigation by spectral analysis. Am J Physiol 1985;249:H867-75.
Elghozi JL, Laude D, Girard A. Effects of respiration on blood pressure and heart rate variability in humans. Clin Exp Pharmacol Physiol 1991;18:735-42.
Lewis GF, Furman SA, McCool MF, Porges SW. Statistical strategies to quantify respiratory sinus arrhythmia: Are commonly used metrics equivalent? Biol Psychol 2012;89:349-64.
Shinba T. Altered autonomic activity and reactivity in depression revealed by heart-rate variability measurement during rest and task conditions. Psychiatry Clin Neurosci 2014;68:225-33.
Kuwahara M, Yayou K, Ishii K, Hashimoto S, Tsubone H, Sugano S. Power spectral analysis of heart rate variability as a new method for assessing autonomic activity in the rat. J Electrocardiol 1994;27:333-7.
Balasubramaniam M, Telles S, Doraiswamy PM. Yoga on our minds: A systematic review of yoga for neuropsychiatric disorders. Front Psychiatry 2012;3:117.
Toschi-Dias E, Tobaldini E, Solbiati M, Costantino G, Sanlorenzo R, Doria S, et al
. Sudarshan Kriya yoga improves cardiac autonomic control in patients with anxiety-depression disorders. J Affect Disord 2017;214:74-80.
Chu IH, Wu WL, Lin IM, Chang YK, Lin YJ, Yang PC. Effects of yoga on heart rate variability and depressive symptoms in women: A randomized controlled trial. J Altern Complement Med 2017;23:310-6.
Morgan JR, Sullivan M, Masuda A, Tully E, Cohen LL, Anderson PL. A case series on the effects of kripalu yoga for generalized anxiety disorder. Int J Yoga Therap 2016;26:9-19.
Department of Psychiatry, Shizuoka Saiseikai General Hospital, 1-1-1 Oshika, Suruga-ku, Shizuoka 422-8527
Source of Support: None, Conflict of Interest: None
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3]
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