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Journal of Zhejiang University-SCIENCE B (Biomedicine & Biotechnology)  2006, Vol. 7 Issue (10): 10-    DOI: 10.1631/jzus.2006.B0844
    
Characterization of surface EMG signals using improved approximate entropy
CHEN Wei-ting, WANG Zhi-zhong, REN Xiao-mei
Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
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Abstract  An improved approximate entropy (ApEn) is presented and applied to characterize surface electromyography (sEMG) signals. In most previous experiments using nonlinear dynamic analysis, this certain processing was often confronted with the problem of insufficient data points and noisy circumstances, which led to unsatisfactory results. Compared with fractal dimension as well as the standard ApEn, the improved ApEn can extract information underlying sEMG signals more efficiently and accurately. The method introduced here can also be applied to other medium-sized and noisy physiological signals.

Key wordsSurface EMG (sEMG) signal      Nonlinear analysis      Approximate entropy (ApEn)      Fractal dimension     
Received: 13 January 2006     
CLC:  R318.04  
Cite this article:

CHEN Wei-ting, WANG Zhi-zhong, REN Xiao-mei. Characterization of surface EMG signals using improved approximate entropy. Journal of Zhejiang University-SCIENCE B (Biomedicine & Biotechnology), 2006, 7(10): 10-.

URL:

http://www.zjujournals.com/xueshu/zjus-b/10.1631/jzus.2006.B0844     OR     http://www.zjujournals.com/xueshu/zjus-b/Y2006/V7/I10/10

[1] CHANG Ying, LIU Qian-jun, ZHANG Jin-song. Flocculation control study based on fractal theory[J]. Journal of Zhejiang University-SCIENCE B (Biomedicine & Biotechnology), 2005, 6(10): 14-.
[2] HU Xiao, WANG Zhi-zhong, REN Xiao-mei. Classification of surface EMG signal with fractal dimension[J]. Journal of Zhejiang University-SCIENCE B (Biomedicine & Biotechnology), 2005, 6( 8): 22-.