Application of Visual Sensing Techniques in Computational Intelligence for Risk Assessment of Sports Injuries in Colleges.

Injury prediction is one of the most challenging issues in sports and is a key component of injury prevention, since successful injury prediction forms the basis for effective preventive measures. In this study, an analysis was made on the risk of physical injuries to college students to guarantee the physical safety of students in sports and improve the quality of physical education. Then, a study was carried out on the occurrences of physical injury risks through visual sensing techniques, and an investigation was conducted into the characteristics of physical injury risks in colleges. Next, the student's body shape and physical characteristics are computed using visual sensing techniques, and the risk of sports injuries is evaluated. The results show that the proposed image recognition and computation methods can accurately identify the sports injuries of college students. Furthermore, it can effectively analyze the factors affecting the risk of sports injuries, and the error of the proposed technique remains between -3 and 2. In addition, it can accurately locate the occurrence of sports injury risks and reduce the impact of those risks in time. This work provides technical support for the reduction of sports injury risks and contributes to the improvement of physical education teaching quality in colleges.