Wavelet transform to recognize muscle fatigue

Abstract

Electromyography (EMG) is to measure the muscle response to nervous stimulation. The power spectrum of the EMG shifts towards lower frequencies during a continued muscle contraction due to muscular fatigue. Muscle fatigue is the decline in ability of a muscle to create force. This research presents the effectiveness of the wavelet transform applied to the surface EMG (SEMG) signal as a means of understanding muscle fatigue during walk. Power spectrum and bispectrum analysis on the EMG signal getting from right rectus femoris muscle is executed utilizing various wavelet functions (WFs). It is possible to recognize muscle fatigue appreciably with the proper choice of the WF. The outcome proves that, the most momentous changes in the EMG power spectrum symbolized by WF Daubechies4. Moreover, bispectrum properties compared to the other WFs. To determine muscle fatigue during gait, Daubechies45 is used in this research to analyze SEMG signal.

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