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Investigation on HRV Signal Dynamics for Meditative Intervention

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Soft Computing: Theories and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1154))

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.

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Author information

Authors and Affiliations

  1. Department of Instrumentation Engineering, Central Institute of Technology, Kokrajhar, Assam, 783370, India

    Dipen Deka

  2. Department of Electronics and Communication Engineering, Tezpur University, Tezpur, Assam, 784028, India

    Bhabesh Deka

Authors
  1. Dipen Deka
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  2. Bhabesh Deka
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Corresponding author

Correspondence to Bhabesh Deka .

Editor information

Editors and Affiliations

  1. Department of Paper Technology, IIT Roorkee, Roorkee, India

    Millie Pant

  2. Graphic Era Hill University, Dehradun, Uttarakhand, India

    Tarun Kumar Sharma

  3. NIT Patna, Patna, India

    Rajeev Arya

  4. NIT Patna, Patna, India

    B.C. Sahana

  5. Ryerson University, Toronto, ON, Canada

    Hossein Zolfagharinia

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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

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