Abstract
Background:
Previous studies of nostril-regulated yoga breathing have focused on unilateral breathing with both inspiration and expiration through a specified nostril. However, traditionally described yoga breathing involves inspiration through one nostril and expiration through the other, called suryabhedan pranayama (SBP) (right nostril inspiration) and chandrabhedan pranayama (CBP) (left nostril inspiration). The effects of these practices were investigated here.
Methods:
Forty-seven healthy male participants (group mean age ± standard deviation [SD]; 26.34 ± 6.38 years) with prior experience of yoga breathing (group mean age ± SD; 43.64 ± 32.84 months) were randomly assigned to four sessions on separate days: (i) SBP, (ii) CBP, (iii) Breath awareness, and (iv) Quiet rest. The heart rate variability (HRV) and breath rate were recorded pre, during, and post each practice.
Results:
There was a significant increase in low frequency (LF) power and SD of NN intervals during SBP and CBP in comparison to the respective preceding (P < 0.05; repeated measures analyses of variance with Bonferroni adjusted post hoc analysis), while LF increased post-CBP alone. During both interventions, there were significant reductions in respiration rate.
Conclusion:
The changes in HRV suggest common rather than distinct changes in SBP and CBP suggestive of respiration-related increased cardiac parasympathetic activity. The involvement of both nostrils in SBP and CBP may have contributed to the comparable effects of the two practices.
Keywords: Cardiac parasympathetic activity, heart rate variability, nostril regulation, respiration rate, yoga breathing
Introduction
The nasal cycle is an ultradian rhythm characterized by a change in the internasal airflow with a phase length ranging between 30 min and 6 h.[1,2] Phases of the nasal cycle are associated with changes in functions regulated by the autonomic nervous system.[3,4] Asymmetrical nasal vasomotor oscillations mediated through oscillations in sympathetic activity are believed to give rise to the nasal cycle and produce both psychological and physiological effects unique to each nostril in humans. Yoga practice includes nostril-regulated breathing, hence allowing for research on these practices for extended periods.[4] Most investigations on nostril-regulated yoga breathing reported the effects of volitionally breathing through one nostril exclusively. There is some support for right uninostril breathing as activating (i.e. increasing oxygen consumed and blood pressure and reducing blood flow to the skin of the hand[5,6] with less clear effects of left uninostril breathing.[5,6,7,8,9]
However, breathing through one nostril exclusively is not mentioned in the ancient yoga texts [viz., Hatha Pradipika Circa 1500 CE[10] and Gheranda Samhita Circa 1700 CE,[11] but is mentioned in present-day commentaries on yoga.[12] In the traditional texts,[10,11] regulated nostril breathing is not unilateral but involves inspiration through one nostril and expiration through the other.[10,11] In the traditional texts, inspiration through the right nostril and expiration through the left nostril (called suryabhedan = surya is the “sun” [hence stimulating] and bhedan means “to pierce”) have been described.[10,11] The corresponding practice (i.e., inspiration through the left nostril with expiration through the right nostril [called chandrabhedan = chandra is the “moon” hence calming]) has evolved in contemporary practice.[10,11]
Unlike uninostril yoga breathing techniques, to our knowledge, there are no reports on how these traditionally described, nostril-regulated yoga breathing practices influence heart rate variability (HRV).
Hence, the present randomized, crossover trial was planned to assess the effects of traditionally described nostril-regulated yoga breathing on the HRV. All participants were assessed in four sessions, namely, right nostril inspiration breathing (suryabhedan pranayama [SBP]), left nostril inspiration breathing (chandrabhedan pranayama [CBP]), breath awareness (BAW) (as an interventional control), and quiet rest (QR) (as a control session) on different days in random order. It was hypothesized that in SBP, the changes would be consistent with the description as activating, whereas in CBP, the changes would be consistent with the description as calming.
Methods
Participants
Forty-seven healthy male participants (group mean age ± standard deviation [SD]; 26.34 ± 6.38 years; with average body mass index ± SD, 21.2 ± 2.2 kg/m2) with ages between 18 and 46 years were recruited for the present study from a state private university in North India. Recruitment was carried out with flyers displayed on notice boards and announcements made in lecture halls. With the sample size of 47, and Cohen’s d of 1.49 (obtained from change in low frequency [LF] power during SBP compared to pre), the power obtained was 1.00 for the present study which was determined using the G-Power program.[13] The criteria for inclusion in the trial were as follows: (i) apparent normal health based on a semi-structured interview and regular clinical examination, (ii) a minimum of 6-month experience practicing yoga breathing as specified in traditional yoga texts,[14] and (iii) participants’ availability for recording on four separate days at the same time of day. The exclusion criteria for the trial were (i) females were excluded from the study to reduce intra-individual variability, based on variations in phases of the menstrual cycle,[15] though this is acknowledged as a limitation of the study, (ii) regular consumption of alcohol or tobacco (in any form), (iii) disturbed sleep routine in the night before the assessment, (iv) intense physical exercise within 24 h of the assessment, and (v) extrasystole in the electrocardiogram (EKG) (to avoid abnormal HRV recordings). The exclusion criteria (ii to v) mentioned above were selected to reduce the variability in HRV based on suggestions for HRV recording.[16] None of the participants were required to be excluded for these reasons. The participants’ signed informed consent forms were taken before enrolment. The study was approved by the institutional ethical committee (YRD-018/007). The baseline characteristics of the participants are provided in Table 1.
Table 1.
Baseline characteristics of the participants
| Characteristics | Details | |
|---|---|---|
| Sample | Number of participants | 47 |
| Gender | Males | |
| Age | Age range (years) | 18-46 |
| Group mean age±SD (years) | 26.34±6.38 | |
| BMI (Kg/M2) | Group mean±SD | 21.16±2.22 |
| Education in years (number) | 10-12 years of education | 27 |
| 15 years of education | 12 | |
| 17 years of education | 8 | |
| Yoga experience | Group average yoga experience±SD (months) | 43.64±32.84 |
| Yoga experience range (months) | 6-144 | |
| Time spent in practicing yoga in a day (in minutes) | Group mean±SD | 98.19±44.24 |
| Marital status | Unmarried (number) | 47 |
| Health status | Presence of any disease (number) | 0 |
| Taking any medication (number) | 0 | |
| Diet | Lacto-vegetarians | 47 |
| Sleep quality | Self-rating of sleep quality on a 10 cm analog scale | 8.80±0.79 |
| Duration of sleep (in minutes) | 338.44±4.22 | |
| Duration of physical activity/day (in minute) | Physical activity in a day (in minutes) | 48.04±58.18 |
| Physical activity in a day range (in minutes) | 8-244 | |
| Tobacco & alcohol | Consumption of tobacco including smoking (number) | 0 |
| Consumption of alcohol (number) | 0 |
Study design
The participants were informed about the schedule of the study. There were three stages of randomization and allocation. (i) A person who was unaware of the study protocol assigned each of the four sessions a serial number from the four digits between 1 and 4. (ii) 47 sets of random sequences of the four digits, namely, 1, 2, 3, and 4, were generated using an online randomizer (www.randomizer.org). (iii) Each of the 47 participants was assigned one sequence of four digits, which determined the order of the four sessions (i.e., SBP, CBP, BAW, and QR) for that participant. The order of the sessions to which the participants were assigned was unknown to the participants. Each session was for 33 min. All sessions were divided into three states: pre, during, and post. (i) The prestate was for 5 min, (ii) the during state was for 18 min (three, 5 min periods of practice with 1 min of rest after each), and (iii) the postperiod of 10 min after the intervention. Figure 1 shows a flow diagram showing the study process flow. Figure 2 shows a schematic representation of the design of the study. The recordings were carried out between January 2020 and March 2021.
Figure 1.
The flow diagram showing the study process flow
Figure 2.
Schematic representation of the design of the study
Assessments
Assessments were carried out at fixed times (i.e., between 05:00 and 07:30 h) in a sound-attenuated and air-conditioned laboratory.[16] Participants were asked to empty their urinary bladder before the beginning of the assessments. HRV and respiration were recorded with a two-channel EKG and respiration recording system (MP 45 BIOPAC Student Lab, BIOPAC System Inc, U. S. A.). The EKG was recorded using Ag/AgCl pregelled electrodes for a standard limb lead III configuration (the right hand was required to manipulate the nostrils; hence the lead III configuration involving the left arm-left leg was selected). Data were acquired at the sampling rate of 1024 Hz and analyzed offline. Noise-free data were included for analysis. The respiration rate was obtained from the recording made with a respiratory stethograph transducer fixed around the trunk 8 cm below the lower costal margin when the participant sat erect and fastened after expiration.
Interventions
The following interventions were given for 18 min each: SBP or right nostril inspiration yoga breathing, CBP or left nostril inspiration yoga breathing, BAW, and QR when the participants lay in a semi-recumbent posture.
Suryabhedan pranayama or right nostril inspiration yoga breathing
The cycle begins with inspiration through the right nostril, followed by an occlusion of the right nostril with the right thumb and expiration through the unoccluded left nostril. The middle and ring fingers of the right hand were used to close the left nostril. All participants were right-hand dominant based on specific questions asked from the participants about their handedness (e.g., which hand do you use to brush your teeth or writing or to throw). There was no retention of breath (kumbhaka) during the practice. (It is to be noted that in the traditional texts, SBP is mentioned as having a period of breath hold between inspiration and expiration).[10,11] The cycle continues. Figure 3 shows a schematic representation of the procedure of SBP.
Figure 3.
Schematic representation of the procedure of suryabhedan Pranayama
Chandrabhedan pranayama or left nostril inspiration yoga breathing
The thumb of the right hand occluded the right nostril. The cycle begins with inspiration through the left nostril, following which the left nostril was occluded with the right middle and ring fingers while expiration through the unoccluded right nostril. The cycle continues. There was no retention of breath (kumbhaka) during the practice. Figure 4 shows a schematic representation of the procedure of CBP.
Figure 4.
Schematic representation of the procedure of chandrabhedan pranayama
Breath awareness
Participants were instructed to pay close attention to the flow of air as it passed through the nasal passage. Participants were told not to change their breathing in any way and to focus solely on the breath. BAW was chosen as an intervention because it is part of all yoga breathing techniques. The breath rate and other aspects of breathing were not altered on purpose.
Quiet rest
During this practice, participants were asked to avoid conscious regulation of their breath or thoughts, which were hence free to wander.
Self-report of ease of practice
A 10-cm horizontal line with word descriptions at both ends served as the scale was used for participants to self-report their ease of practice.[17] “Worst possible” and “Excellent” were the two adjectives used at the end of the line. Participants were asked to judge their ease of practice immediately after each of the four sessions by placing a vertical mark on a horizontal line that represented how well they were able to follow the practice instructions.
Data extraction
Heart rate variability
The data were visually inspected for movement artifacts, if any. None of the data were required to be edited for movement artifacts. The square root of the mean of the sum of the squares of differences between adjacent NN intervals (RMSSD) and the SD of NN intervals (SDNN) were noted. Furthermore, the power in the HRV series for the LF band (0.04–0.15 Hz) and the high frequency band (0.15–0.40 Hz) were determined. LF power, HF power, SDNN, and RMSSD were transformed to natural logarithm to standardize the data and have been presented as log-transformed low-frequency component power (LnLF), log-transformed high frequency component power (LnHF), log-transformed standard deviation of the N-N interval (LnSDNN), and log-transformed root mean square of successive differences between normal heartbeats (LnRMSSD), respectively, in the results section. The respiration rate was calculated as the average number of breaths/minutes (bpm).
Ease of practice
Participants’ scores for their ease to practice the yoga breathing techniques were obtained by measuring the distance between the participant’s mark on the line and the end anchored with “not satisfactory,” using a standard measuring scale. A higher score indicated better ease of practice. If the score was <7.0, the session was repeated. None of the sessions had to be repeated for this reason.
Statistical analysis
Statistical analyses were done using separate repeated measures analyses of variance (RM-ANOVA) through IBM SPSS Version 24.0 (IBM SPSS [Version 24.0], New York, USA) followed by post hoc analyses with Bonferroni adjustment. Each RM-ANOVA had two “Within subjects” factors, i.e. Sessions (with four levels; SBP, CBP, BAW, and QR) and States (with six levels, i.e. pre, during 1, during 2, during 3, post 1, and post 2). The level of significance (α) was set at 0.05 (two-tailed).
Results
Forty-seven healthy male participants were assigned to four randomly ordered sessions on separate days. The group mean ± SD values for the ease of practice assessed with the visual analog scale were (i) 9.03 ± 1.27 for SBP, (ii) 8.99 ± 1.09 for CBP, (iii) 8.69 ± 1.28 for BAW, and (iv) 8.97 ± 1.33 for QR. The baseline characteristics of the participants are presented in Table 1.
Repeated measures analyses of variance
There was a significant difference between States for (i) LnLF (Huynh-Feldt: F1.46,67.10 = 6.33, P = 0.007), (ii) LnSDNN (Huynh-Feldt: F3.46,159.33 = 12.88, P < 0.001), and (iii) respiration rate (bpm) (Huynh-Feldt: F2.64,121.58 = 46.47, P < 0.001). A significant difference between Sessions was noted for (i) LnLF (Huynh-Feldt: F1.54,71.00 = 7.01, P = 0.004), (ii) LnSDNN (Huynh-Feldt: F3,138 = 6.52, P < 0.001), and (iii) respiration rate (bpm) (Huynh-Feldt: F2.54,117.01 = 26.64, P < 0.001). Furthermore, a significant interaction between Sessions × States was found in (i) LnSDNN (Huynh-Feldt: F9.06, 416.56 = 5.62, P < 0.001), and (ii) respiration rate (bpm) (Huynh-Feldt: F7.95,365.82 = 20.42, P < 0.001).
Post hoc analyses
The LnLF increased in the three during states (i.e. during 1, during 2, and during 3) for (i) SBP (P < 0.001, with 95% confidence interval [CI] of [−0.826, −1.792] for during 1; P < 0.001, with 95% CI of [−0.764, −1.713] for during 2; P < 0.001, with 95% CI of [−0.864, −1.784] for during 3) and (ii) CBP (P < 0.001, with 95% CI of [−0.475, −1.703] for during 1; P < 0.001, with 95% CI of [−0.431, −1.572] for during 2; P < 0.001, with 95% CI of [−0.665, −1.621] for during 3; P = 0.004, with 95% CI of [−0.109, −0.918] for post 1). The LnRMSSD decreased in the poststate for SBP (P = 0.015, with 95% CI of [0.309, 0.020] for post1). The LnSDNN increased in the three during states (i.e. during 1, during 2, and during 3) for (i) SBP (P < 0.001, with 95% CI of [−0.110, −0.477] for during 1; P < 0.001, with 95% CI of [−0.109, −0.479] for during 2; P < 0.001, with 95% CI of [−0.128, −0.505] for during 3) and (ii) CBP (P = 0.051, with 95% CI of [0.0004, −0.443] for during 1; P = 0.001, with 95% CI of [−0.084, −0.433] for during 2; P = 0.011, with 95% CI of [−0.039, −0.495] for during 3). The respiration rate (bpm) decreased in the three during states (i.e. during 1, during 2, and during 3) for (i) SBP (P < 0.001, with 95% CI of [5.471, 2.920] for during 1; P < 0.001, with 95% CI of [4.861, 2.191] for during 2; P < 0.001, with 95% CI of [5.095, 2.300] for during 3) and (ii) CBP (P < 0.001, with 95% CI of [4.825, 2.387] for during 1; P < 0.001, with 95% CI of [4.204, 1.547] for during 2; P < 0.001, with 95% CI of [4.437, 1.897] for during 3).
The group mean ± SD for (i) LnLF, (ii) LnHF, (iii) LnRMSSD, (iv) LnSDNN, and (v) respiration rate (bpm) pre, during, and postyoga breathing (i.e. SBP, CBP, BAW and QR) are given in Table 2.
Table 2.
Values of the (i) LnLF, (ii) LnHF, (iii) LnRMSSD, (iv) LnSDNN, and (v) Respiration rate (bpm) in the four sessions. Data presented as mean±SD
| Variables | States | Suryabhedan pranayama (SBP) | Chandrabhedan pranayama (CBP) | Breath awareness (BAW) | Quiet rest (QR) |
|---|---|---|---|---|---|
| LnLF | Pre | 7.10±0.91 | 7.18±1.11 | 7.11±1.08 | 6.95±1.02 |
| During 1 | 8.40±0.92*** | 8.27±1.05*** | 7.38±1.16 | 7.24±0.77 | |
| During 2 | 8.33±0.96*** | 8.18±0.94*** | 7.45±0.96 | 7.29±1.01 | |
| During 3 | 8.42±0.86*** | 8.32±0.85*** | 7.45±1.01 | 7.17±1.02 | |
| Post 1 | 7.22±0.99 | 7.69±0.99** | 7.32±0.98 | 7.16±1.03 | |
| Post 2 | 7.31±0.94 | 7.56±0.99 | 8.50±7.80 | 7.18±0.91 | |
| LnHF | Pre | 7.32±1.11 | 7.53±1.37 | 7.27±1.27 | 7.33±1.29 |
| During 1 | 7.25±1.20 | 7.23±1.59 | 7.22±1.12 | 7.45±0.97 | |
| During 2 | 7.24±1.14 | 7.38±1.65 | 7.31±1.07 | 7.51±1.09 | |
| During 3 | 7.39±1.24 | 7.33±1.44 | 7.12±1.00 | 7.41±1.19 | |
| Post 1 | 7.16±0.98 | 7.50±1.10 | 7.33±1.17 | 7.41±1.14 | |
| Post 2 | 7.33±1.00 | 7.56±1.18 | 7.19±1.17 | 7.40±1.07 | |
| LnRMSSD | Pre | 4.33±0.52 | 4.39±0.63 | 4.40±0.53 | 4.34±0.58 |
| During 1 | 4.33±0.50 | 4.31±0.67 | 4.30±0.51 | 4.28±0.50 | |
| During 2 | 4.29±0.56 | 4.38±0.67 | 4.30±0.50 | 4.35±0.50 | |
| During 3 | 4.37±0.57 | 4.38±0.68 | 4.28±0.49 | 4.34±0.51 | |
| Post 1 | 4.17±0.50* | 4.29±0.65 | 4.27±0.57 | 4.32±0.55 | |
| Post 2 | 4.28±0.50 | 4.33±0.55 | 4.22±0.51 | 4.27±0.56 | |
| LnSDNN | Pre | 4.14±0.43 | 4.19±0.52 | 4.19±0.45 | 4.11±0.52 |
| During 1 | 4.43±0.39*** | 4.41±0.46* | 4.23±0.49 | 4.11±0.43 | |
| During 2 | 4.43±0.42*** | 4.45±0.43** | 4.15±0.51 | 4.16±0.44 | |
| During 3 | 4.46±0.39*** | 4.46±0.48** | 4.20±0.42 | 4.18±0.43 | |
| Post 1 | 4.07±0.41 | 4.24±0.42 | 4.14±0.46 | 4.15±0.49 | |
| Post 2 | 4.14±0.41 | 4.21±0.46 | 4.12±0.42 | 4.12±0.45 | |
| Respiration rate (bpm) | Pre | 15.54±2.03 | 15.44±1.92 | 15.34±2.31 | 15.78±2.02 |
| During 1 | 11.34±2.64*** | 11.83±2.62*** | 14.45±3.07 | 16.11±1.86 | |
| During 2 | 12.01±2.83*** | 12.57±2.56*** | 14.77±2.85 | 15.80±1.87 | |
| During 3 | 11.84±3.02*** | 12.27±2.44*** | 14.81±2.65 | 15.67±2.01 | |
| Post 1 | 14.72±2.46 | 14.91±2.09 | 15.59±2.24 | 15.67±2.11 | |
| Post 2 | 15.05±2.15 | 15.21±1.94 | 15.45±1.95 | 15.52±2.00 |
*P<0.05, **P<0.01, ***P<0.001; Multiple comparisons with post hoc (Bonferroni) adjustment when pre values were compared with D1, D2, D3 and post values of the respective session
Discussion
The two breathing practices (i.e. SBP and CBP) had comparable effects. This finding was contrary to the hypothesized unique effects of each breathing practice. The changes included an increase in LF and SDNN during both SBP and CBP compared to the respective preceding values.
The LF band (0.04–0.15 Hz) is believed to be generated by (i) both parasympathetic and sympathetic nervous system activity, or (ii) by parasympathetic nervous system activity alone,[18,19,20,21,22] or (iii) by baroreflex activity alone.[23] During periods of slow respiration, vagal activity generates oscillations in the heart rhythm within the LF band frequency. Hence, respiratory-related, efferent, vagally mediated influences are present in the LF band when breathing with a slow respiration rate.[24,25] SDNN is also contributed to by both the sympathetic and parasympathetic nervous systems.[26,27] However, in short-term recordings of around 5 min involving slow regulated breathing, as in the present study, the main source of SDNN is parasympathetically-mediated respiratory sinus arrhythmia.[27,28]
In the present study, the respiration rates during the two yoga breathing practices were significantly lower than the respective preceding baselines, i.e., suryabhedan (breath rate 11.7 breaths per minute, a decrease of 3.8 breaths per minute compared to the preceding state) and chandrabhedan (breath rate 12.2 breaths per minute, a decrease of 3.2 breaths per minute compared to the preceding state). Hence, activity due to the lower frequency respiration may have contributed to the increased LF band activity, even though the contribution of respiration to the LF band usually occurs when the breath frequency is <9 breaths per minute.[29]
The common changes in HRV during the two yoga breathing practices may be related to the way, in which nostril regulation was carried out. Unlike earlier studies on nostril-regulated yoga breathing which involved unilateral airflow through either the left or right nostril exclusively,[5,6,7,8] in the present study, the two breathing techniques involved a “crossover of airflow” through both nostrils in different phases of respiration. The mechanism for unilateral breathing influencing the autonomic nervous system is not precisely understood. In early reports, asymmetrical changes in sympathetic activity led to vasomotor changes in the nostrils leading to asymmetrical patency and occlusion in the nostrils in the spontaneously breathing cat.[30,31] Similar mechanisms were believed to underlie the nasal cycle in spontaneously breathing humans.[7] The nasal cycle is associated with a wide range of physiological activities,[32] including axillary sweat production,[33] pupil size,[34] rhinal activity,[34] rhythms of the neuroendocrine, cardiovascular and insulin systems,[35,36] and with brain activity.[3] More recent research also supports that breathing through specific nostrils influences brain activity with specificity, i.e. left-nostril and nondominant breathing (usually the left-nostril) being associated with greater EEG power in posterior areas of the brain.[4] The connection between nostril patency and these physiological effects is unclear. The changeover in airflow through the nostrils during inhale–exhale in both yoga breathing practices studied here (i.e. right nostril inspiration yoga breathing and left nostril inspiration yoga breathing) may activate both nostrils equally leading to common rather than unique physiological effects. As an application in health, both traditionally described nostril-regulated breathing practices can be practiced to increase cardiac vagus nerve activity and counter the physiological effects of stress, irrespective of whether the practice begins with right nostril inspiration or left nostril inspiration.
Limitations
The findings are limited to short-term effects of the breathing practices, with no longitudinal follow-up or yoga-naïve group for comparison. Furthermore, the generalizability of the findings is limited by selecting yoga-experienced, male participants alone.
Conclusion
In summary, the two yoga breathing practices, namely, right nostril inspiration yoga breathing and left nostril inspiration yoga breathing are associated with increased respiration-related cardiac parasympathetic activity. Hence, in nostril breathing with a crossover between nostrils during inspiration–expiration, there appear to be common rather than unique effects.
Ethical statement
The approval of the Institutional Ethics Committee was obtained (approval number YRD 018/007).
Conflicts of interest
There are no conflicts of interest.
Funding Statement
Nil.
References
- 1.Hanif J, Jawad SS, Eccles R. The nasal cycle in health and disease. Clin Otolaryngol Allied Sci. 2000;25:461–7. doi: 10.1046/j.1365-2273.2000.00432.x. [DOI] [PubMed] [Google Scholar]
- 2.White DE, Bartley J, Nates RJ. Model demonstrates functional purpose of the nasal cycle. Biomed Eng Online. 2015;14:38. doi: 10.1186/s12938-015-0034-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Werntz DA, Bickford RG, Bloom FE, Shannahoff-Khalsa DS. Alternating cerebral hemispheric activity and the lateralization of autonomic nervous function. Hum Neurobiol. 1983;2:39–43. [PubMed] [Google Scholar]
- 4.Jeong H, Choo MS, Cho MC, Son H, Yoo S. Prediction of surgical margin status and location after radical prostatectomy using positive biopsy sites on 12-core standard prostate biopsy. Sci Rep. 2022;12:4066. doi: 10.1038/s41598-022-08022-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Telles S, Nagarathna R, Nagendra HR. Breathing through a particular nostril can alter metabolism and autonomic activities. Indian J Physiol Pharmacol. 1994;38:133–7. [PubMed] [Google Scholar]
- 6.Telles S, Nagarathna R, Nagendra HR. Physiological measures of right nostril breathing. J Altern Complement Med. 1996;2:479–84. doi: 10.1089/acm.1996.2.479. [DOI] [PubMed] [Google Scholar]
- 7.Shannahoff-Khalsa D. Lateralized rhythms of the central and autonomic nervous systems. Int J Psychophysiol. 1991;11:225–51. doi: 10.1016/0167-8760(91)90017-r. [DOI] [PubMed] [Google Scholar]
- 8.Bhavanani AB, Ramanathan M, Balaji R, Pushpa D. Differential effects of uninostril and alternate nostril pranayamas on cardiovascular parameters and reaction time. Int J Yoga. 2014;7:60–5. doi: 10.4103/0973-6131.123489. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Malhotra V, Srivastava R, Parasuraman P, Javed D, Wakode S, Thakare A, et al. Immediate autonomic changes during right nostril breathing and left nostril breathing in regular yoga practitioners. J Educ Health Promot. 2022;11:280. doi: 10.4103/jehp.jehp_343_22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Muktibodhananda S. Bihar: Bihar School of Yoga; 2002. Hatha Yoga Pradipika: Light on Hatha Yoga. [Google Scholar]
- 11.Saraswati N. Bihar: Bihar School of Yoga; 2012. Gheranda Samhita: Commentary on the Yoga Teachings of Maharshi Gheranda. [Google Scholar]
- 12.Muktibodhananda S. Bihar: Bihar School of Yoga; 1999. Swara Yoga: The Tantric Science of Brain Breathing. [Google Scholar]
- 13.Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39:175–91. doi: 10.3758/bf03193146. [DOI] [PubMed] [Google Scholar]
- 14.Ramdev S. Haridwar: Divya Prakashan Divya Yog Mandir (Trust); 2009. Pranayama Rahasya with Scientific Factual Evidence; p. 100. [Google Scholar]
- 15.Das TK, Jana H. Basal oxygen consumption during different phases of menstrual cycle. Indian J Med Res. 1991;94:16–9. [PubMed] [Google Scholar]
- 16.Laborde S, Mosley E, Thayer JF. Heart rate variability and cardiac vagal tone in psychophysiological research – Recommendations for experiment planning, data analysis, and data reporting. Front Psychol. 2017;8:213. doi: 10.3389/fpsyg.2017.00213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Wewers ME, Lowe NK. A critical review of visual analogue scales in the measurement of clinical phenomena. Res Nurs Health. 1990;13:227–36. doi: 10.1002/nur.4770130405. [DOI] [PubMed] [Google Scholar]
- 18.Akselrod S, Gordon D, Ubel FA, Shannon DC, Berger AC, Cohen RJ. Power spectrum analysis of heart rate fluctuation: A quantitative probe of beat-to-beat cardiovascular control. Science. 1981;213:220–2. doi: 10.1126/science.6166045. [DOI] [PubMed] [Google Scholar]
- 19.Hua K, Zhang J, Wakana S, Jiang H, Li X, Reich DS, et al. Tract probability maps in stereotaxic spaces: Analyses of white matter anatomy and tract-specific quantification. Neuroimage. 2008;39:336–47. doi: 10.1016/j.neuroimage.2007.07.053. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Berntson GG, Cacioppo JT, Grossman P. Whither vagal tone. Biol Psychol. 2007;74:295–300. doi: 10.1016/j.biopsycho.2006.08.006. [DOI] [PubMed] [Google Scholar]
- 21.Lehrer PM. Biofeedback training to increase heart rate variability. In: Lehrer PM, Woolfolk RL, Sime WE, editors. Principles and Practice of Stress Management. New York, NY: Guilford Press; 2007. pp. 227–48. [Google Scholar]
- 22.Reyes del Paso GA, Langewitz W, Mulder LJ, van Roon A, Duschek S. The utility of low frequency heart rate variability as an index of sympathetic cardiac tone: A review with emphasis on a reanalysis of previous studies. Psychophysiology. 2013;50:477–87. doi: 10.1111/psyp.12027. [DOI] [PubMed] [Google Scholar]
- 23.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. doi: 10.1113/expphysiol.2010.056259. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Brown TE, Beightol LA, Koh J, Eckberg DL. Important influence of respiration on human R-R interval power spectra is largely ignored. J Appl Physiol (1985) 1993;75:2310–7. doi: 10.1152/jappl.1993.75.5.2310. [DOI] [PubMed] [Google Scholar]
- 25.Tiller WA, McCraty R, Atkinson M. Cardiac coherence: A new, noninvasive measure of autonomic nervous system order. Altern Ther Health Med. 1996;2:52–65. [PubMed] [Google Scholar]
- 26.Umetani K, Singer DH, McCraty R, Atkinson M. Twenty-four hour time domain heart rate variability and heart rate: Relations to age and gender over nine decades. J Am Coll Cardiol. 1998;31:593–601. doi: 10.1016/s0735-1097(97)00554-8. [DOI] [PubMed] [Google Scholar]
- 27.Shaffer F, Ginsberg JP. An overview of heart rate variability metrics and norms. Front Public Health. 2017;5:258. doi: 10.3389/fpubh.2017.00258. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Shaffer F, McCraty R, Zerr CL. A healthy heart is not a metronome: An integrative review of the heart’s anatomy and heart rate variability. Front Psychol. 2014;5:1040. doi: 10.3389/fpsyg.2014.01040. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Kromenacker BW, Sanova AA, Marcus FI, Allen JJ, Lane RD. Vagal mediation of low-frequency heart rate variability during slow yogic breathing. Psychosom Med. 2018;80:581–7. doi: 10.1097/PSY.0000000000000603. [DOI] [PubMed] [Google Scholar]
- 30.Eccles R, Lee RL. The influence of the hypothalamus on the sympathetic innervation of the nasal vasculature of the cat. Acta Otolaryngol. 1981;91:127–34. [Google Scholar]
- 31.Eccles JS, Adler TF, Futterman R, Goff SB, Kaczala CM, Meece JL, et al. Expectancies, values, and academic behaviors. In: Spence JT, editor. Achievement and Achievement Motivation: Psychological and Sociological Approaches. San Francisco CA: W. H. Freeman and Company; 1983. pp. 75–146. [Google Scholar]
- 32.Kahana-Zweig R, Geva-Sagiv M, Weissbrod A, Secundo L, Soroker N, Sobel N. Measuring and characterizing the human nasal cycle. PLoS One. 2016;11:e0162918. doi: 10.1371/journal.pone.0162918. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Leclerc J, Doyle WJ, Karnavas WJ. The relationship between the nasal cycle and axillary sweat production. Rhinology. 1987;25:249–57. [PubMed] [Google Scholar]
- 34.Beickert P. Asymmetry of vegetative innervations. Archives of Otolaryngology, Nose and Throat Medicine. 1951;157:404–11. [Google Scholar]
- 35.Shannahoff-Khalsa DS, Kennedy B, Yates FE, Ziegler MG. Low-frequency ultradian insulin rhythms are coupled to cardiovascular, autonomic, and neuroendocrine rhythms. Am J Physiol. 1997;272:R962–8. doi: 10.1152/ajpregu.1997.272.3.R962. [DOI] [PubMed] [Google Scholar]
- 36.Shannahoff-Khalsa DS, Kennedy B, Yates FE, Ziegler MG. Ultradian rhythms of autonomic, cardiovascular, and neuroendocrine systems are related in humans. Am J Physiol. 1996;270:R873–87. doi: 10.1152/ajpregu.1996.270.4.R873. [DOI] [PubMed] [Google Scholar]