Research on Knee Injuries in College Football Training Based on Artificial Neural Network | IEEE Conference Publication | IEEE Xplore

Research on Knee Injuries in College Football Training Based on Artificial Neural Network


Abstract:

In recent years, the number of students receiving football training in colleges has been increasing, however, during football trainings in most colleges and universities,...Show More

Abstract:

In recent years, the number of students receiving football training in colleges has been increasing, however, during football trainings in most colleges and universities, high-intensity sports are generally performed. Therefore, the athletes often experience knee injury during training, which is harmful to the health of athletes and affects football players' professional skills improvement. This paper analyzes the reasons for the knee injuries of college football trainees, based on the artificial neural network technology and through the method of data analysis. This paper finds that football muscle damage types mainly include the medial collateral ligament, meniscus injury, anterior cruciate ligament, the knee bursitis, enthesopathy of the patellar tendon, and the lateral collateral ligament and Sinding Larsen and chondromalacia patellae these seven types.
Date of Conference: 11-13 December 2020
Date Added to IEEE Xplore: 08 February 2021
ISBN Information:
Conference Location: Shenyang, China

I. Introduction

Athletes' injuries affect the athletes' physical and mental health to varying degrees, which is harmful to the improvement of athletes' sports performance. In the process of football training, the probability of getting knee injury is gradually increasing, which has always been one of the factors that influence college football training [1]. The combination of artificial neural network with college football training offers a method of using artificial neural network to strengthen football training, and uses artificial neural network to solve the problem of knee injury during football training, which is beneficial to improve the training efficiency of football players [2]. Taking the soccer robot as the research object, the artificial neural network is used to construct the soccer robot behavior decision-making and basic action learning model, and the methods of improving artificial neural network is discussed to provide a certain foundation for football training. At the same time, in order to improve the selection of high-level football players, based on artificial neural network, the paper analyzes 23 comprehensive indicators of college football players, including the basic quality, body and function and so on, and offers the selection model of football players, which further lays a good foundation for college football training.

References

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