ARTIFICIAL INTELLIGENCE–BASED MARKERLESS MOTION CAPTURE AND BIOMECHANICAL ANALYSIS: PROSPECTS FOR APPLICATION IN PHYSICAL EDUCATION AND SPORTS PRACTICE (THE CASE OF WOMEN’S UNEVEN BARS)

Abstract

This article discusses the introduction of artificial intelligence–based markerless motion capture and biomechanical analysis technologies into physical education and sports practice. The study was conducted using the example of exercises performed on the women’s uneven bars in artistic gymnastics. Using video analysis and computer vision technologies, joint angles, body posture, balance, and movement stability were evaluated. Biomechanical indicators were compared with the athletes’ fatigue state. In addition, the advanced experience of the Russian University of Sport “GTSOLIFK” (formerly RGUFK) and leading sports science centers in the United States was analyzed. The results show that artificial intelligence–based analysis methods effectively help physical education teachers and coaches to identify technical errors at an early stage, plan training loads correctly, and reduce the risk of injuries.