Artificial Intelligence in the Auxiliary Guidance Function of Athletes’ Movement Standard Training in Physical Education

Abstract

Artificial Intelligence (AI) is a new technical science that studies and develops theories, methods, techniques and application systems for simulating, extending and expanding human intelligence. This paper is based on the research of AI in the auxiliary guidance function of athletes’ standard training in physical education. It aims to conduct data mining from different aspects such as different joint angular speeds, motion injury screening and different parts of sports injuries and then integrate these aspects. Create a way to reduce athletes’ injuries and scientific training. In order to improve the recognition efficiency of athletes’ movement patterns, nonlinear auto regressive neural networks are used to recognize the movement patterns of athletes’ limb surface signals. Through this research work, it can provide a certain reference basis and practice platform for the research on the auxiliary guidance role of AI in the sports standard training of athletes in physical education. Performance design and implementation include four modules: Image acquisition, preprocessing, motion detection and human motion recognition. Between them, the image acquisition module uses a memory mapping path to determine the format of the camera frame image, and the image format conversion is completed through channel conversion. Experimental data shows that athletes’ strength quality, speed of action response, technical continuity, psychological stability and physical control ability have all been greatly improved. Among them, the most obvious is that with the assistance of AI technology, the psychological stability has reached 9.2; the strength quality has reached 9.1.

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