Analysis of Joint Injury Prevention in Basketball Overload Training Based on Adjustable Embedded Systems

Abstract

Basketball is a competitive sport, and athletes often choose to increase training intensity and difficulty in order to achieve better results. This inevitably leads to joint damage. Therefore, this study aims to explore prevention strategies for joint injuries during basketball overload training based on adjustable embedded systems. This study proposes a prevention strategy based on an adjustable embedded system to address the issue of athlete joint injuries during basketball overload training. This system integrates advanced sensor technology and real-time data analysis algorithms, aiming to monitor and analyze key parameters of basketball players during overload training in real time. The system consists of adjustable hardware devices and intelligent software platforms, which can accurately capture key information such as athlete’s motion data, strength output, and joint angles. Based on the results of real-time data analysis, the system can intelligently adjust training intensity, frequency, and methods. In addition, the system can provide personalized training suggestions based on the individual characteristics and training goals of athletes, helping them improve their technical movements and optimize training effectiveness. Through extensive experimental verification and practical application, this study demonstrates the effectiveness of joint injury prevention strategies for basketball overload training based on adjustable embedded systems. This system can not only effectively prevent joint injuries among athletes, but also improve the scientific and targeted nature of training, providing strong support for the training of basketball players.