Quantitative estimation of muscle fatigue using surface electromyography during static muscle contraction
Yewguan Soo, Masao Sugi, Mizuki Nishino, Hiroshi Yokoi, Tamio Arai, Ryu Kato, Tomohiko Nakamura, Jun Ota
Abstract
Yewguan Soo, Masao Sugi, Mizuki Nishino, Hiroshi Yokoi, Tamio Arai, Ryu Kato, Tomohiko Nakamura, Jun Ota
Abstract
Muscle fatigue is commonly associated with the musculoskeletal disorder problem. Previously, various techniques were proposed to index the muscle fatigue from electromyography signal. However, quantitative measurement is still difficult to achieve. This study aimed at proposing a method to estimate the degree of muscle fatigue quantitatively. A fatigue model was first constructed using handgrip dynamometer by conducting a series of static contraction tasks. Then the degree muscle fatigue can be estimated from electromyography signal with reasonable accuracy. The error of the estimated muscle fatigue was less than 10% MVC and no significant difference was found between the estimated value and the one measured using force sensor. Although the results were promising, there were still some limitations that need to be overcome in future study.
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Muscle fatigue is commonly associated with the musculoskeletal disorder problem. Previously, various techniques were proposed to index the muscle fatigue from electromyography signal. However, quantitative measurement is still difficult to achieve. This study aimed at proposing a method to estimate the degree of muscle fatigue quantitatively. A fatigue model was first constructed using handgrip dynamometer by conducting a series of static contraction tasks. Then the degree muscle fatigue can be estimated from electromyography signal with reasonable accuracy. The error of the estimated muscle fatigue was less than 10% MVC and no significant difference was found between the estimated value and the one measured using force sensor. Although the results were promising, there were still some limitations that need to be overcome in future study.
Key concepts: Electromyography, Muscle fatigue, Muscle contraction, Physical medicine and rehabilitation, SIGNAL (programming language), Dynamometer, Computer science, Biomedical engineering