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CLC number: R318.04

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Received: 2005-01-04

Revision Accepted: 2005-05-30

Crosschecked: 0000-00-00

Cited: 28

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Citations:  Bibtex RefMan EndNote GB/T7714

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Journal of Zhejiang University SCIENCE B 2005 Vol.6 No.8 P.844-848


Classification of surface EMG signal with fractal dimension

Author(s):  HU Xiao, WANG Zhi-zhong, REN Xiao-mei

Affiliation(s):  Department of Biomedical Engineering, Shanghai Jiaotong University, Shanghai 200030, China

Corresponding email(s):   huxiaocz@sjtu.edu.cn

Key Words:  Surface EMG signal, Fractal dimension, Correlation dimension, Self-similarity, GP algorithm

HU Xiao, WANG Zhi-zhong, REN Xiao-mei. Classification of surface EMG signal with fractal dimension[J]. Journal of Zhejiang University Science B, 2005, 6(8): 844-848.

@article{title="Classification of surface EMG signal with fractal dimension",
author="HU Xiao, WANG Zhi-zhong, REN Xiao-mei",
journal="Journal of Zhejiang University Science B",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Classification of surface EMG signal with fractal dimension
%A HU Xiao
%A WANG Zhi-zhong
%A REN Xiao-mei
%J Journal of Zhejiang University SCIENCE B
%V 6
%N 8
%P 844-848
%@ 1673-1581
%D 2005
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2005.B0844

T1 - Classification of surface EMG signal with fractal dimension
A1 - HU Xiao
A1 - WANG Zhi-zhong
A1 - REN Xiao-mei
J0 - Journal of Zhejiang University Science B
VL - 6
IS - 8
SP - 844
EP - 848
%@ 1673-1581
Y1 - 2005
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2005.B0844

Surface EMG (electromyography) signal is a complex nonlinear signal with low signal to noise ratio (SNR). This paper is aimed at identifying different patterns of surface EMG signals according to fractal dimension. Two patterns of surface EMG signals are respectively acquired from the right forearm flexor of 30 healthy volunteers during right forearm supination (FS) or forearm pronation (FP). After the high frequency noise is filtered from surface EMG signal by a low-pass filter, fractal dimension is calculated from the filtered surface EMG signal. The results showed that the fractal dimensions of filtered FS surface EMG signals and those of filtered FP surface EMG signals distribute in two different regions, so the fractal dimensions can represent different patterns of surface EMG signals.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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