Features for muscle fatigue computed from electromyogram and mechanomyogram: A new one

Abstract

Muscle fatigue produces negative effects in the performance and it may lead to a muscle failure. This problem makes the quantitative grading of muscle fatigue a necessity in ergonomic and physiological research. Moreover, the quantitative grading of muscle fatigue is needed to increase work and sport productivity and prevent several accidents that result from muscle fatigue. Even though there are many studies for this aim, there is no quantitative criterion for the evaluation of muscle fatigue. The main reason is that muscle fatigue is a complex physiological situation that is dependent on several parameters. Our aim in this study is to present a new feature to evaluate muscle fatigue and prove the reliability of the new feature by making correlation analyses between this with other features. For this aim, electromyography and mechanomyography signals were simultaneously recorded from the biceps brachii and triceps brachii muscles during the isometric and isotonic contractions of 60 healthy volunteers (30 females, 30 males). The mean power frequency and median frequency, which are used in the literature, were compared to the frequency ratio change, the new measure; correlations between the frequency ratio change and the mean power frequency and median frequency were analysed. There was a high correlation between the features, and frequency ratio change can be used to quantitatively evaluate muscle fatigue.

Keywords

Frequency ratio change isotonic isometric discrete wavelet transform Pearson correlation analysis

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