DocumentCode
2652738
Title
Study on fatigue feature from forearm SEMG signal based on wavelet analysis
Author
Wan, Baikun ; Xu, Lifeng ; Ren, Yue ; Wang, Lu ; Qiu, Shuang ; Liu, Xiaojia ; Liu, Xiuyun ; Qi, Hongzhi ; Ming, Dong ; Wang, Weijie
Author_Institution
Dept. of Biomed. Eng., Tianjin Univ., Tianjin, China
fYear
2010
fDate
14-18 Dec. 2010
Firstpage
1229
Lastpage
1232
Abstract
The aim of this paper is to estimate muscle fatigue by using wavelet analysis method in SEMG signal analysis. A signal acquisition system is designed and forearm muscle fatigue experiments under static and dynamic contractions are performed. The wavelet analysis method is proposed to group the wavelet coefficients of SEMG signal into high frequency-band (100Hz-350Hz) and low frequency-band (13-22Hz). The amplitude of SEMG signal is determined by calculating the root mean square, the amplitude of high frequency is correlated to the force level and the amplitude of low frequency band which is correlated to the muscle fatigue shows an upward trend. Then correlation coefficients between RMS of low frequency band and MF, RMS of low frequency band and MDF in static contraction as well the first time-varying parameter in dynamic contraction are calculated. Results demonstrate that the wavelet analysis method is an effective analysis tool in muscle fatigue evaluation and it lays a foundation for studying at the muscle fatigue in a variety of muscle contraction modes.
Keywords
correlation methods; electromyography; feature extraction; medical signal detection; wavelet transforms; correlation coefficient; dynamic contraction; fatigue feature; forearm SEMG signal analysis; muscle fatigue estimation; signal acquisition; static contraction; surface electromyography; wavelet analysis; Correlation; Dynamics; Fatigue; Force; Muscles; Time frequency analysis; Wavelet analysis; RMS; correlation; muscle fatigue; wavelet analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Biomimetics (ROBIO), 2010 IEEE International Conference on
Conference_Location
Tianjin
Print_ISBN
978-1-4244-9319-7
Type
conf
DOI
10.1109/ROBIO.2010.5723504
Filename
5723504
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