Application of higher order statistics/spectra in biomedical signals-A review

被引：205

作者：

Chua, Kuang Chua ^{[1
]}

Chandran, Vinod ^{[2
]}

Acharya, U. Rajendra ^{[1
]}

Lim, Choo Min ^{[1
]}

机构：

[1] Ngee Ann Polytech, Dept Elect & Comp Engn, Singapore 599489, Singapore

[2] Queensland Univ Technol, Brisbane, Qld 4001, Australia

来源：

MEDICAL ENGINEERING & PHYSICS | 2010年 / 32卷 / 07期

关键词：

Higher order spectra; Spectrum; Electrocardiogram; Heart rate variability; Electroencephalogram; Epilepsy; Entropy; Linearity; Stationary; Gaussianity; Bispectrum; Bicoherence; SPECTRAL-ANALYSIS; EEG SIGNALS; EMG SIGNALS; BISPECTRUM; CLASSIFICATION; INVARIANTS; COMPONENTS;

D O I：

10.1016/j.medengphy.2010.04.009

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

For many decades correlation and power spectrum have been primary tools for digital signal processing applications in the biomedical area. The information contained in the power spectrum is essentially that of the autocorrelation sequence; which is sufficient for complete statistical descriptions of Gaussian signals of known means. However, there are practical situations where one needs to look beyond autocorrelation of a signal to extract information regarding deviation from Gaussianity and the presence of phase relations. Higher order spectra, also known as polyspectra, are spectral representations of higher order statistics, i.e. moments and cumulants of third order and beyond. HOS (higher order statistics or higher order spectra) can detect deviations from linearity, stationarity or Gaussianity in the signal. Most of the biomedical signals are non-linear, non-stationary and non-Gaussian in nature and therefore it can be more advantageous to analyze them with HOS compared to the use of second-order correlations and power spectra. In this paper we have discussed the application of HOS for different bio-signals. HOS methods of analysis are explained using a typical heart rate variability (HRV) signal and applications to other signals are reviewed. (C) 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

引用

页码：679 / 689

页数：11

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