Abstract
Heart rate variability (HRV) has been a very useful marker in unfolding the activity of the autonomic nervous system (ANS) for different actions and state of the human mind. With the continuous uprise in the meditation/yoga practitioners, for its well-known positive impacts on overall well-being, we have intended to find scientific evidences behind it. On that account, we have computed three nonlinear parameters, named increment entropy, fluctuation coefficient, and degree of dispersion to characterize the complex dynamical behaviour of HRV signal during meditation obtained from PhysioNet database. Further, time and frequency domain parameters are also evaluated to establish its correlation with nonlinear measures. The results from the analysis have demonstrated a decrease in the chaotic complexity and dynamics of the HRV signal during meditation, which can be used as a reliable tool in detecting diseases related to cardiology, endocrinology, and psychiatry.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bussing, A., Michalsen, A., Khalsa, S.B.S., Telles, S., Sherman, K.J.: Effects of yoga on mental and physical health: a short summary of reviews. Evid. Based Complement. Alternat. Med. 2012(165410), 1–7 (2012)
Tyagi, A., Cohen, M.: Yoga and hypertension: a systematic review. Altern. Ther. Health Med. 20, 32–59 (2014)
Tyagi, A., Cohen, M.: Yoga and heart rate variability: a comprehensive review of the literature. Int. J. Yoga. 9, 97–113 (2016)
Li, A.W., Goldsmith, C.A.: The effects of yoga on anxiety and stress. Altern. Med. Rev. 17, 21–35 (2012)
Lugo, J., Doti, R., Faubert, J.: The Fulcrum principle between parasympathetic and sympathetic peripheral systems: Auditory noise can modulate body’s peripheral temperature. In: Pant, M., Ray, K., Sharma, T., Rawat, S., Bandyopadhyay, A. (eds.) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol. 584, pp. 333–342. Springer, Singapore (2018)
Terathongkum, S., Pickler, R.H.: Relationships among heart rate variability, hypertension, and relaxation techniques. J. Vasc. Nurs. 22(3), 78–82 (2004)
Kamath, C.: Analysis of heart rate variability signal during meditation using deterministic-chaotic quantifiers. J. Med. Eng. Technol. 37(7), 436–448 (2013)
Goshvarpour, A., Goshvarpour, A.: Poincare indices for analyzing meditative heart rate signals. Biomed J. 38(3), 229–234 (2015)
Singh, R.S., Saini, B.S., Sunkaria, R.K.: Power spectral analysis of short-term heart rate variability in healthy and arrhythmia subjects by the adaptive continuous morlet wavelet transform. Appl. Med. Inform. 39(3–4), 49–66 (2017)
Malik, M., Camm, A.J., Bigger, J.T., Breithardt, G., Cerutti, S., Cohen, R.J.: Heart rate variability: standards of measurement, physiological interpretation, and clinical use. Eur. Heart J. 17(3), 354–381 (1996)
Raghavendra, B.S., Dutt, D.N.: Nonlinear dynamical characterization of heart rate variability time series of meditation. Int. J. Biomed. Biol. Eng. 5(9), 429–440 (2011)
Bhatt, A., Dubey, S.K., Bhatt, A.: Analytical study on cardiovascular health issues prediction using decision model-based predictive analytic techniques. In: Pant, M., Ray, K., Sharma, T., Rawat, S., Bandyopadhyay, A. (eds.) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol. 584, pp. 289–299. Springer, Singapore (2018)
Kleiger, R., Stein, P.K., Bigger, J.T.: Heart rate variability: measurement and clinical utility. Ann. Noninvasive Electrocardiol. 10, 88–101 (2005)
Shaffer, F., Ginsberg, J.P.: An overview of heart rate variability metrics and norms. Front. Public Health 5(258) (2017)
Vinutha, H.T., Raghavendra, B.R., Manjunath, N.K.: Effect of integrated approach of yoga therapy on autonomic functions in patients with type 2 diabetes. Indian J. Endocrinol. Metab. 19(5), 653–657 (2018)
Yao, W., Zhang, Y., Wang, J.: Quantitative analysis in nonlinear dynamic complexity detection of meditative heart beats. Phys. A 512, 1060–1068 (2018)
Goswami, D.P., Bhattacharya, D.K., Tibarewala, D.N.: Analysis of heart rate variability in meditation using normalized shannon entropy. Int. J. Phys. Sci. 14(1), 61–67 (2010)
Liu, X., Jiang, A., Xu, N., Xue, J.: Increment entropy as a measure of complexity for time series. Entropy 18(22), 1–14 (2016)
Schiepek, G., Strunk, G.: The identification of critical fluctuations and phase transitions in short term and coarse-grained time series-a method for the real-time monitoring of human change processes. Biol. Cybern. 102, 197–207 (2010)
Peng, C., Mietus, J., Liu, Y., Khalsa, G., Douglas, P., Benson, H., Goldberger, A.: Exaggerated heart rate oscillations during two meditation techniques. Int. J. Cardiol. 70(2), 101–107 (1999)
Peter, R., Sood, S., Dhawan, A.: Spectral parameters of HRV in yoga practitioners, athletes and sedentary males. Indian J. Physiol. Pharmacol. 59(4), 380–387 (2015)
Bonello, J., Garg, L., Garg, G., Audu, E.: Effective data acquisition for machine learning algorithm in EEG signal processing. In: Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing (2018)
Bhaduri, A., Ghosh, D.: Quantitative assessment of heart rate dynamics during meditation: an ECG based study with multi-fractality and visibility graph. Front. Physiol. 7(44), 1–10 (2016)
Jiang, S., Bian, C., Ning, X., Ma, Q.D.Y.: Visibility graph analysis on heartbeat dynamics of meditation training. Appl. Phys. Lett. 102, 253–702 (2013)
Dey, A., Bhattacharya, D.K., Tibarewala, D., Dey, N., Ashour, A.S., Le, D.N., Gospodinova, E., Gospodinov, M.: Chinese-chi and Kundalini yoga meditations effects on the autonomic nervous system: comparative study. Int. J. Interact. Multimedia Artif. Intell. 3(7), 87–95 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Deka, D., Deka, B. (2020). Investigation on HRV Signal Dynamics for Meditative Intervention. In: Pant, M., Kumar Sharma, T., Arya, R., Sahana, B., Zolfagharinia, H. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 1154. Springer, Singapore. https://doi.org/10.1007/978-981-15-4032-5_89
Download citation
DOI: https://doi.org/10.1007/978-981-15-4032-5_89
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-4031-8
Online ISBN: 978-981-15-4032-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)