EMG signal filtering based on Empirical Mode Decomposition

被引：135

作者：

Andrade, Adriano O. ^{[1
]}

Nasuto, Slawomir ^{[1
]}

Kyberd, Peter ^{[2
]}

Sweeney-Reed, Catherine M. ^{[1
]}

Van Kanijn, F. R. ^{[1
]}

机构：

[1] Univ Reading, Sch Syst Engn, Dept Cybernet, Reading RG6 6AY, Berks, England

[2] Univ New Brunswick, Fredericton, NB E3B 5A3, Canada

来源：

BIOMEDICAL SIGNAL PROCESSING AND CONTROL | 2006年 / 1卷 / 01期

关键词：

Electromyography; Empirical Mode Decomposition; Wavelets; Adaptive filters;

D O I：

10.1016/j.bspc.2006.03.003

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This paper introduces a procedure for filtering electromyographic (EMG) signals. Its key element is the Empirical Mode Decomposition, a novel digital signal processing technique that can decompose my time-series into a set of functions designated as intrinsic mode functions. The procedure for EMG signal filtering is compared to a related approach based on the wavelet transform. Results obtained from the analysis of synthetic and experimental EMG signals show that Our method can be Successfully and easily applied in practice to attenuation of background activity in EMG signals. (c) 2006 Elsevier Ltd. All rights reserved.

引用

页码：44 / 55

页数：12

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