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Inverse Correlation between Heart Rate Variability and Heart Rate Demonstrated by Linear and Nonlinear Analysis

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  • Syed Zaki Hassan Kazmi
  • Henggui Zhang
  • Wajid Aziz
  • Oliver Monfredi
  • Syed Ali Abbas
  • Saeed Arif Shah
  • Syeda Sobia Hassan Kazmi
  • Wasi Haider Butt

Abstract

The dynamical fluctuations in the rhythms of biological systems provide valuable information about the underlying functioning of these systems. During the past few decades analysis of cardiac function based on the heart rate variability (HRV; variation in R wave to R wave intervals) has attracted great attention, resulting in more than 17000-publications (PubMed list). However, it is still controversial about the underling mechanisms of HRV. In this study, we performed both linear (time domain and frequency domain) and nonlinear analysis of HRV data acquired from humans and animals to identify the relationship between HRV and heart rate (HR). The HRV data consists of the following groups: (a) human normal sinus rhythm (n = 72); (b) human congestive heart failure (n = 44); (c) rabbit sinoatrial node cells (SANC; n = 67); (d) conscious rat (n = 11). In both human and animal data at variant pathological conditions, both linear and nonlinear analysis techniques showed an inverse correlation between HRV and HR, supporting the concept that HRV is dependent on HR, and therefore, HRV cannot be used in an ordinary manner to analyse autonomic nerve activity of a heart.

Suggested Citation

  • Syed Zaki Hassan Kazmi & Henggui Zhang & Wajid Aziz & Oliver Monfredi & Syed Ali Abbas & Saeed Arif Shah & Syeda Sobia Hassan Kazmi & Wasi Haider Butt, 2016. "Inverse Correlation between Heart Rate Variability and Heart Rate Demonstrated by Linear and Nonlinear Analysis," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-10, June.
    • Handle: RePEc:plo:pone00:0157557
    DOI: 10.1371/journal.pone.0157557
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    Cited by:

    1. Kenneth Y. T. Lim & Minh Anh Nguyen Duc & Minh Tuan Nguyen Thien & Rajamanickam Yuvaraj & Jack S. Fogarty, 2022. "Investigating the Effects of Microclimate on Physiological Stress and Brain Function with Data Science and Wearables," Sustainability, MDPI, vol. 14(17), pages 1-35, August.
    2. Syed Zaki Hassan Kazmi & Nazneen Habib & Rabia Riaz & Sanam Shahla Rizvi & Syed Ali Abbas & Tae-Sun Chung, 2020. "Multiscale based nonlinear dynamics analysis of heart rate variability signals," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-14, December.

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