AUTHOR=Sun Jiaqi , Liu Guangda , Sun Yubing , Lin Kai , Zhou Zijian , Cai Jing TITLE=Application of Surface Electromyography in Exercise Fatigue: A Review JOURNAL=Frontiers in Systems Neuroscience VOLUME=16 YEAR=2022 URL=https://www.frontiersin.org/journals/systems-neuroscience/articles/10.3389/fnsys.2022.893275 DOI=10.3389/fnsys.2022.893275 ISSN=1662-5137 ABSTRACT=

Exercise fatigue is a common physiological phenomenon in human activities. The occurrence of exercise fatigue can reduce human power output and exercise performance, and increased the risk of sports injuries. As physiological signals that are closely related to human activities, surface electromyography (sEMG) signals have been widely used in exercise fatigue assessment. Great advances have been made in the measurement and interpretation of electromyographic signals recorded on surfaces. It is a practical way to assess exercise fatigue with the use of electromyographic features. With the development of machine learning, the application of sEMG signals in human evaluation has been developed. In this article, we focused on sEMG signal processing, feature extraction, and classification in exercise fatigue. sEMG based multisource information fusion for exercise fatigue was also introduced. Finally, the development trend of exercise fatigue detection is prospected.