Effectiveness of an AI-Supported Sports-Educational Rehabilitation Program in Improving Motor Performance and Reducing Low Back Pain among Physical Education Students

Abstract

Background: Low back pain is among the most prevalent musculoskeletal disorders in sports and educational settings, negatively impacting motor performance and physical activity participation. Despite notable advances in digital rehabilitation technologies, the integration of artificial intelligence into sports-educational rehabilitation programs remains a field lacking comprehensive systematic studies, particularly in the context of physical education students.

Objective: To evaluate the effectiveness of an AI-supported sports-educational rehabilitation program in improving motor performance and alleviating low back pain among physical education students.

Methodology: The study adopted an experimental design with two groups (experimental and control), comprising 60 students who underwent the program for 12 weeks at a rate of three sessions per week, with an AI platform employed for real-time monitoring and feedback. The Functional Movement Screen (FMS) and the Oswestry Disability Index (ODI) were used to assess the study variables.

Results: Findings revealed statistically significant differences (p < 0.01) in favor of the experimental group in motor performance (d = 1.14) and pain reduction (d = 0.98), with a digital adherence rate of 87.3% compared to 61.2% in the control group.

Conclusion: The proposed program presents an innovative rehabilitation model that integrates digital technologies with sports-educational practice, thereby enhancing prospects for generalization across educational institutions and sports rehabilitation programs