Research on Athlete Posture Monitoring and Correction Technology Based on Wireless Sensing and Computer Vision Algorithms

Abstract

In sports training and competition, the traditional methods of athlete posture monitoring often rely on complex equipment and expensive technology, which is difficult to be widely used. This study aims to explore a posture monitoring and correction technology based on wireless sensing and computer vision algorithms to provide a low-cost, efficient and easy-to-use solution. In this study, wireless sensors are used to collect real-time data of athletes during training and competition, and computer vision algorithms are combined to analyze athletes' posture. The wireless sensors include an inertial measurement unit (IMU) that captures the athlete's movement trajectory and changes in Angle. Using computer vision technology, the video images of athletes are obtained by cameras, and the posture recognition and dynamic analysis are carried out. Data fusion method combines sensor data with visual data to improve the accuracy and reliability of posture monitoring. The experimental results show that the posture monitoring system based on wireless sensing and computer vision algorithm can accurately identify and evaluate the athlete's posture. The system can feedback athletes' postural deviation in real time, provide effective correction suggestions, and significantly improve athletes' postural performance.