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Spectral Analysis of Heart Rate Variability Based on the Hilbert-Huang Method.

A A Grinevich1, N K Chemeris2

  • 1Institute of Cell Biophysics, Russian Academy of Sciences, Pushchino, Russia. grin_aa@mail.ru.

Doklady. Biochemistry and Biophysics
|October 13, 2023
PubMed
Summary

The Hilbert-Huang method offers a new way to analyze heart rate variability (HRV), revealing distinct spectral components for better understanding heart regulation systems.

Keywords:
Hilbert–Huang methodcardiovascular systemheart rate variabilitywavelet analysis

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Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Noninvasive Physiology

Background:

  • Heart rate variability (HRV) analysis is crucial for assessing cardiac autonomic regulation.
  • Current methods like Fourier analysis provide averaged spectral parameters within fixed frequency bands.
  • Limitations exist in precisely defining the boundaries of regulatory system influences on HRV.

Purpose of the Study:

  • To evaluate the Hilbert-Huang method for spectral parameter calculation in HRV analysis.
  • To compare the capabilities of the Hilbert-Huang method against traditional Fourier analysis.
  • To explore novel approaches for quantifying HRV oscillations.

Main Methods:

  • Application of the Hilbert-Huang transform for analyzing HRV data.
  • Identification and characterization of spectral components using Gaussian functions.
  • Comparative analysis with established Fourier transform techniques for HRV.

Main Results:

  • The Hilbert-Huang method identified four distinct spectral components of HRV oscillations.
  • These components were described by Gaussian functions, indicating concentrated energy.
  • The study demonstrated the absence of rigid boundaries between these spectral components.
  • Quantitative energy characteristics of these components were derived.

Conclusions:

  • The Hilbert-Huang method provides a more detailed spectral analysis of HRV.
  • The identified spectral components and their energy characteristics offer potential for novel diagnostic tools.
  • This approach can supplement existing methods for assessing heart rhythm regulation.
  • Further research into these quantitative characteristics could enhance diagnostic capabilities.