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Study on fatigue feature from forearm SEMG signal based on wavelet analysis | IEEE Conference Publication | IEEE Xplore

Study on fatigue feature from forearm SEMG signal based on wavelet analysis


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 f...Show More

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.
Date of Conference: 14-18 December 2010
Date Added to IEEE Xplore: 03 March 2011
ISBN Information:
Conference Location: Tianjin, China

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