Analysis and prevention and treatment of ankle joint injury factors in basketball players based on data mining
Abstract
Basketball, as a highly popular ball game, has become increasingly exciting in both time and space. Therefore, basketball players must have good physical fitness. They need to adapt to changing environments and master corresponding technical actions. In sports, it is usually necessary to break away from the opponent’s defense by moving quickly and stopping quickly. Defensive players must make accurate predictions based on the enemy’s technical movements, which are often accompanied by intense physical confrontation. The purpose of this study is to analyze the causes and characteristics of ankle joint injuries in basketball players, propose treatment suggestions and preventive measures, and prevent ankle joint injuries. Firstly, the reasons for ankle joint injuries were explained, and a brief analysis was made of the characteristics of ankle joint injuries in the project and the technical actions that can easily cause ankle joint injuries. Next, this article considers preventive measures to avoid ankle joint injuries and proposes methods for preventing and treating ankle joint injuries during exercise. Afterwards, data mining methods were used to study the research mechanism of ankle joint injury, in order to promote the research mechanism of ankle joint injury. Through experiments and analysis, RBF neural network algorithm was introduced into the ankle joint injury research mechanism, and the new ankle joint injury research mechanism could enhance the therapeutic effect by 10.7%.
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