Application of back propagation neural network in sports fatigue indicators

Abstract

Introduction: High-intensity rehabilitation training will produce exercise fatigue. Objective: A backpropa-gation (BP) network neural algorithm is proposed to predict sports fatigue based on electromyography (EMG) signal images. Methods: The principal component analysis algorithm is used to reduce the dimension of EMG signal features. The knee joint angle is estimated by the regularized over-limit learning machine algorithm and the BP neural network algorithm. Results: The RMSE value of the regularized over-limit learning machine algorithm is lower than that of the BP neural network algorithm. At the same time, the ρ value of the regularized over-limit learning machine algorithm is closer to 1, indicating its higher accuracy. Conclusions: The model training time of the regularized over-limit learning machine algorithm has been greatly reduced, which improves efficiency. Level of evidence II; Therapeutic studies-investigation of treatment results.