Cardiac state diagnosis using higher order spectra of heart rate variability

被引：110

作者：

Division of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore 590011, Singapore ^{[1
]}

不详 ^{[2
]}

机构：

[1] Division of Electronics and Computer Engineering, Ngee Ann Polytechnic

[2] School of Engineering Systems, Queensland University of Technology, Brisbane

来源：

J. Med. Eng. Technol. | 2008年 / 2卷 / 145-155期

关键词：

Bicoherence; Bispectrum; Entropy; Heart rate; Statistics;

D O I：

10.1080/03091900601050862

中图分类号：

学科分类号：

摘要：

Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart, by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computer-based intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are nonlinear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of nonlinear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and seven classes of arrhythmia. We present some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. We also extracted features from the HOS and performed an analysis of variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value <0.02 in the ANOVA test. © 2008 Informa UK Ltd.

引用

页码：145 / 155

页数：10

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