A Study of University Sports Training Methods Assisted by Artificial Intelligence

At present, the traditional sports equipment technology program in colleges and universities is unreasonable, and the sports training management mode is obsolete, so it is not possible to provide scientific guidance to students’ sports. In this study, a Kinect sensing device is used to collect movement data of college students in sports training, and the skeletal features extracted from the movement data are extracted using the space vector method. The hidden Markov model is used to identify and model skeletal features, and the results of action recognition in sports training are obtained. Finally, an intelligent feedback system for sports training has been developed to assist in the guidance and formulation of university sports training programs. It was found that after 17 weeks of sports training based on the sports training intelligent system, the physical fitness level of university students and the scores of functional movement assessment in sports training were substantially improved, and there was a significant difference between the students under the traditional training program. This verifies the assistive effect of the intelligent system on university sports training and provides some reference for intelligent and scientific sports training.