Prediction simulation of sports injury based on embedded system and neural network

摘要

Sports injury prediction is one of the most important parts of the challenge of prevention and harm challenging in motion. Sports injury contemplated wherein a simplified view of the phenomenon to study the reduction unit's cause. A linear analysis is viewed as the unidirectional manner a substantial portion of, and causality. This reduction method depends on the correlation and regression analysis. Despite the extensive efforts to predict sports injuries, the existing method is the inability to identify the predictors that were and have been limited. The risk of the very important element for sports players' injury when developing prevention and risk mitigation strategies for work-related accidents. Some signs can be used in many ways to identify risk factors for injury. However, it can be made from the data and lead to incorrect inferences and difficulty understanding the nuances of different statistical methods. The proposed Neural Network (NN) and the embedded system classify the sports player's injury prediction to solve the problem. The proposed Neural Network (NN) and the embedded system have attracted a simple calculation and interpretation of the reliable results for sports injury prediction. The simulation results show the high performance compared to other existing methods.