Non-Linear Signal Processing Techniques Applied on EMG Signal for Muscle Fatigue Analysis During Dynamic Contraction

In the field of ergonomics, biomechanics, sports and rehabilitation muscle fatigue is regarded as an important aspect for study. Work postures are basically dynamic in nature. Classical signal processing techniques used to understand muscle behavior are mainly based on spectral based parameters estimation, and mostly applied during static contraction. But fatigue analysis in dynamic conditions is of utmost requirement because of its daily life applicability. It is really difficult to consistently find the muscle fatigue during dynamic contraction due to the inherent non stationarity time-variant nature and associated noise in the signal along with complex physiological changes in muscles. Nowadays, different non-linear signal processing techniques are adopted to find out the consistent and robust indicator for muscle fatigue under dynamic condition considering the high degree of non stationarity in the signal. In this paper, various nonlinear signal processing methods, applied on surface EMG signal for muscular fatigue analysis, under dynamic contraction are discussed.

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