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Pulse signal analysis of patients with coronary heart diseases using Hilbert-Huang transformation and time-domain

Fu-feng Li1, Ren Sun, Song Xue

  • 1Syndrome Laboratory of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China.

Chinese Journal of Integrative Medicine
|May 4, 2015
PubMed

Insights

Pulse signal analysis using Hilbert-Huang transformation (HHT) and time-domain methods can identify coronary heart disease (CHD). Specific pulse wave characteristics and time-domain parameters effectively distinguish CHD patients from controls.

Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Signal Processing

Background:

  • Coronary heart disease (CHD) diagnosis relies on invasive methods.
  • Non-invasive diagnostic tools for CHD are highly sought after.

Purpose of the Study:

  • To investigate pulse signal characteristics for distinguishing CHD patients from non-CHD individuals and healthy controls.
  • To assess the diagnostic potential of pulse signals for CHD.

Main Methods:

  • Collected pulse signals from 407 patients (205 CHD, 202 non-CHD) and 62 healthy controls.
  • Analyzed pulse signals using Hilbert-Huang transformation (HHT) and time-domain analysis.
  • Processed time-domain parameters using ANOVA (SNK test).

Main Results:

  • Identified distinct pulse signal patterns in the CHD group, including increased time-domain parameters (h1, h3, h4, h3/h1, ts, t4/t) and wider pulse width (w).
  • Observed chaotic and disordered C2 waves (44%) and irregular C waves (72%) with amplitudes over 10 g-forces in the CHD group via HHT.
  • These findings showed significant differences compared to control groups.

Conclusions:

  • Characteristic pulse waves and time-domain parameters, extracted via HHT and time-domain analysis, can serve as non-invasive indicators for assessing CHD.
  • Pulse signal analysis shows promise as a non-invasive diagnostic approach for coronary heart disease.
Abstract

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