Classification of surface EMG signal using relative wavelet packet energy

被引：84

作者：

Hu, X ^{[1
]}

Wang, ZZ ^{[1
]}

Ren, XM ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Dept Biomed Engn, Shanghai 200030, Peoples R China

来源：

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE | 2005年 / 79卷 / 03期

基金：

中国国家自然科学基金;

关键词：

action surface EMG signal; wavetet packet transform; relative wavelet packet energy; pattern recognition; motor unit action potential;

D O I：

10.1016/j.cmpb.2005.04.001

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Features can be classified into interferential features and discriminable features according to their contribution to pattern recognition. In this paper, a novel and simple method based on wavelet packet transform is proposed to extract the features from surface EMG signal. In this method, the features are relative wavelet packet energy (RWPE), which is evaluated from several selected frequency bands of surface EMG signal. Compared with a conventional method, which is of the best performance in previous applications, the method can compress the interferential features and enhance the discriminable features more effectively. In consequence, the RWPE features calculated by the method represent different patterns of surface EMG signal more accurately and the accuracy of surface EMG signal pattern classification is improved greatly. (c) 2005 Elsevier Ireland Ltd. All rights reserved.

引用

页码：189 / 195

页数：7

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