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An improved method to evaluate heart rate variability based on time-variant cardiorespiratory relation.

Binbin Liu1, Saisai Yan1, Xiaoni Wang1

  • 1The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.

Journal of Applied Physiology (Bethesda, Md. : 1985)
|June 21, 2019
PubMed
Summary

This study introduces a new method to analyze heart rate variability (HRV) by accounting for respiration. The corrected analysis better distinguishes between parasympathetic (PNS) and sympathetic (SNS) nervous system activity, improving autonomic nervous system (ANS) evaluation.

Keywords:
autonomic nervous systemempirical mode decompositionheart rate variabilityrespiratory slopetime-frequency analysis

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Area of Science:

  • Physiology
  • Autonomic Nervous System Research
  • Cardiovascular Dynamics

Background:

  • Traditional frequency domain analysis of heart rate variability (HRV) using high-frequency (HF) and low-frequency (LF) bands has limitations in accurately assessing parasympathetic (PNS) and sympathetic (SNS) nervous system activity.
  • The influence of respiration on cardiac autonomic activity is significant, affecting the interpretation of standard HRV parameters.
  • A need exists for improved methods to disentangle the contributions of PNS and SNS to HRV for a more precise evaluation of the autonomic nervous system (ANS).

Purpose of the Study:

  • To develop and validate a corrected method for HRV analysis that better distinguishes between PNS and SNS contributions.
  • To incorporate the time-varying relationship between respiration and heart rate into HRV analysis.
  • To establish new indices for evaluating PNS and SNS activity and their balance.

Main Methods:

  • Decomposition of heart rate (HR) into respiration-related (HRr) and respiration-unrelated (HRru) components using empirical mode decomposition (EMD).
  • Time-frequency analysis applied to HRr and HRru to derive respiration-locked (HFr) and respiration-unrelated (LFru) components, respectively.
  • Validation using experimental datasets representing SNS and PNS activation.

Main Results:

  • The corrected HRV analysis demonstrated improved prediction of ANS activity.
  • HFr emerged as a reliable index for PNS activity.
  • LFru primarily reflected SNS activity, and the LFru/HFr ratio provided a more accurate measure of sympathovagal balance.

Conclusions:

  • The proposed method, by correcting HRV components based on respiration, significantly enhances the evaluation of sympathetic and parasympathetic nervous system activity.
  • HFr and LFru serve as valuable indices for assessing PNS and SNS function, respectively.
  • The LFru/HFr ratio offers a more accurate representation of the sympathovagal balance compared to traditional HRV parameters.