Influence mechanism of running sportswear fatigue based on BP neural network

Abstract

The fatigue of running sportswear is reflected in the fatigue caused by the tightness of the tights on the skin surface of the limbs, trunk, and other parts during long-term running sports. However, the current research on the fatigue of running sportswear is not deep enough. Therefore, the purpose of this study is to study the mechanism of the fatigue of running sportswear based on BP neural network. This article first takes sportswear as the starting point and uses the surface myoelectricity index as a physiological quantity as a means to combine clothing with sports medicine and sports physiology, breaking the traditional shackles of subjective assessment of fatigue, and giving play to the advantages of interdisciplinary to expand the new direction of the apparel industry and, secondly, use muscle fatigue evaluation method to analyze the muscles of the lower leg under the pressure of sportswear to analyze the strength of the EMG signal and the number of participating sports units and the frequency of discharge synchronization. Experimental data shows that the AUC is 0.756 when wearing sports tights, the sensitivity and specificity are 72% and 19%, and the accuracy is 65%. The experimental results show that clothing pressure affects the fatigue of running sportswear based on BP neural network.

Neuromuscular Fatigue Responses of Endurance- and Strength-Trained Athletes during Incremental Cycling Exercise

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Training Load Prediction in Physical Education Teaching Based on BP Neural Network Model

“…If the precision is achieved, the algorithm ends. Otherwise, a new learning sample and the expected output are selected and transferred to a step to enter the next round of learning [27]. ere are various parameters of the BPNN algorithm, which are explained as follows:…”

Application of Surface Electromyography in Exercise Fatigue: A Review

“…Muscle strength declines progressively during exercise, so fatigue occurs before the task failure ( Gandevia, 2001 ). There are many examples of application fields involving muscle fatigue, including sports ( Simsek, 2017 ; Kuniszyk-Jozkowiak et al, 2018 ; Liu et al, 2019 ; Hedayatpour et al, 2021 ; Liu and Li, 2021 ; Rodriguez-Rosell et al, 2021 ), rehabilitation ( Gaudet et al, 2018 ; Kim et al, 2018 ; Meng et al, 2019 ; Na et al, 2020 ; Fundaro et al, 2021 ; Sato et al, 2021 ), and occupation ( Alberto et al, 2018 ; Fang et al, 2021 ; Ji and Huang, 2021 ; Yu et al, 2021 ; Gonzalez-Zamora et al, 2022 ). Physiological signals, biochemical assessments, and questionnaires are used to monitor exercise fatigue ( Halson and Shona, 2014 ).…”