Video-based AI system for automatic range of motion assessment in Physical Education and sport
DOI:
https://doi.org/10.47197/retos.v74.117535Keywords:
artificial intelligence, educational technology, primary education, pose estimation, sports biomechanicAbstract
Introduction: ROM is a critical indicator of musculoskeletal health, flexibility, and motor performance, yet its assessment in schools has been constrained by manual methods such as goniometers, which are time-intensive, subjective, and impractical for large groups.
Objective: This study aimed to develop and validate a video-based artificial intelligence (AI) system for automatic Range of Motion (ROM) assessment in physical education.
Methodology: Leveraging advances in AI and computer vision, particularly pose estimation algorithms such as MediaPipe and OpenPose, this research designed a system capable of capturing and analyzing joint movements through standard video recordings on smartphones and laptops. Using the 4D Holistic Model (Define, Design, Develop, Disseminate), the study systematically identified teacher needs, built a prototype with automated angle calculation and real-time feedback, and conducted iterative expert validation and classroom pilot testing.
Results: The results demonstrated that the system provides accurate, efficient, and user-friendly assessments while reducing teacher workload and enhancing instructional precision. Practical implementation highlighted benefits for both teachers through streamlined monitoring and individualized instruction and students, who gained objective progress feedback and improved motivation.
Discussion: While challenges remain regarding lighting conditions, teacher readiness, and data privacy, the system represents a cost-effective and scalable innovation for integrating AI into physical education.
Conclusions: The findings underscore its potential to transform assessment practices, foster physical literacy, and support healthier student development in school contexts.
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Copyright (c) 2025 Muchamad Arif Al Ardha, Kukuh Pambuka Putra, Julian Sahertian, Andhega Wijaya, Sauqi Sawa Bikalawan, Firman Yahya Simanjuntak, Ilham Khefi Ramdhanu, Chung Bing Yang
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