Hilbert-huang transform for analysis of heart rate variability in cardiac health

Helong LI, Sam KWONG, Lihua YANG, Daren HUANG, Dongping XIAO

Research output: Journal PublicationsJournal Article (refereed)peer-review

76 Citations (Scopus)

Abstract

This paper introduces a modified technique based on Hilbert-Huang transform (HHT) to improve the spectrum estimates of heart rate variability (HRV). In order to make the beat-to-beat (RR) interval be a function of time and produce an evenly sampled time series, we first adopt a preprocessing method to interpolate and resample the original RR interval. Then, the HHT, which is based on the empirical mode decomposition (EMD) approach to decompose the HRV signal into several monocomponent signals that become analytic signals by means of Hilbert transform, is proposed to extract the features of preprocessed time series and to characterize the dynamic behaviors of parasympathetic and sympathetic nervous system of heart. At last, the frequency behaviors of the Hilbert spectrum and Hilbert marginal spectrum (HMS) are studied to estimate the spectral traits of HRV signals. In this paper, two kinds of experiment data are used to compare our method with the conventional power spectral density (PSD) estimation. The analysis results of the simulated HRV series show that interpolation and resampling are basic requirements for HRV data processing, and HMS is superior to PSD estimation. On the other hand, in order to further prove the superiority of our approach, real HRV signals are collected from seven young health subjects under the condition that autonomic nervous system (ANS) is blocked by certain acute selective blocking drugs: atropine and metoprolol. The high-frequency power/total power ratio and low-frequency power/high-frequency power ratio indicate that compared with the Fourier spectrum based on principal dynamic mode, our method is more sensitive and effective to identify the low-frequency and high-frequency bands of HRV. © 2011 IEEE.
Original languageEnglish
Pages (from-to)1557-1567
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume8
Issue number6
DOIs
Publication statusPublished - 2011
Externally publishedYes

Bibliographical note

The authors would like to thank the anonymous reviewers for their helpful comments and suggestions which led to the improvement of the results and the presentation of this paper. This work is supported by the Fundamental Research Funds for the Central Universities, SCUT (2009ZM0081), NSFC(10826053, 60825306, U0735004), GDSF(07118074), City University of Hong Kong Strategic Grant (7002441), and RGC General Research Fund 9041236 CityU 114707. This paper is an expanded version of preliminary paper “Application of Hilbert-Huang transform to heart rate variability analysis” presented at International Conference of IEEE on Bioinformatics and Biomedical Engineering and “HRV signal analysis and processing based on Hilbert-Huang transform” presented Journal of Shenzhen University Science and Engineering.

Keywords

  • empirical mode decomposition (EMD)
  • heart rate variability (HRV)
  • Hilbert marginal spectrum (HMS)
  • Hilbert-Huang transform (HHT)
  • interpolation
  • resampling
  • spectrum estimation

Fingerprint

Dive into the research topics of 'Hilbert-huang transform for analysis of heart rate variability in cardiac health'. Together they form a unique fingerprint.

Cite this