Affiliations: [a]
Shandong University Sports Institute, Jinan, Shandong, China
| [b] School of Physical Education, Cangzhou Normal University, Cangzhou, Hebei, China
| [c] China Triathlon Association, Beijing, China
| [d] College of Physical Education, Guangzhou University, Guangzhou, Guangdong, China
Correspondence:
[*]
Corresponding author. Yan Xiong, College of Physical Education, Guangzhou University, Guangzhou, Guangdong, China. E-mail: [email protected].
Abstract: Dress fatigue can affect the efficiency of sports, especially for running, the dress fatigue has a greater impact on it. Moreover, at present, there are few studies on dress fatigue. Based on this, this study is based on BP neural network, and uses surface electromyography theory and muscle fatigue measurement method to perform fatigue measurement. The fatigue threshold analysis is mainly carried out by the experimental method, and the prediction model of the wearing fatigue threshold based on BP neural network is constructed based on the actual demand. Moreover, this paper verifies the reliability of threshold distribution by experimental analysis combined with model analysis. In addition, the study sets the organizational structure and clothing pressure as verification indicators to analyze the performance of the model. The research results show that the model constructed in this study can effectively analyze the mechanism of fatigue impact of running dress, and this paper can provide reference for the study of dress fatigue.
Keywords: BP neural network, running movement, dress fatigue, impact mechanism
