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Biomechanical Analysis Technologies in Physical Education: A Systematic Review of Motion Analysis, Markerless AI, and Virtual Laboratories

1 Department of Physical Education, Health, and Recreation, Universitas Negeri Makassar, Makassar, Indonesia
2 Department of Elementary School Teacher Education, Universitas Muhammadiyah Makassar, Makassar, Indonesia
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Abstract

The rapid digitalization of education and the ongoing decline in youth physical activity have increased pressure for physical education (PE) to shift from observation-based instruction to analytically grounded, responsive teaching methods. Biomechanical analysis technologies facilitate this shift by making movement visible, measurable, and understandable for teachers and students. This review synthesizes recent research on how these technologies are being used to innovate PE, focusing on low-cost video analysis, AI markerless pose estimation, and virtual labs. A systematic review of peer-reviewed studies published between 2017 and 2025 was conducted, using keywords related to biomechanics, PE, Kinovea, Dartfish, pose estimation, AI, and virtual labs, sourced from Google Scholar, ScienceDirect, and PubMed. After screening titles, abstracts, and full texts against established criteria, 53 studies were included in the primary analysis; recent publications from 2026 were also included to investigate emerging implications. The review found that affordable motion analysis tools like Kinovea and Dartfish support formative feedback and reflective learning; AI-based markerless systems such as OpenPose, MediaPipe, MoveNet, and RTMPose enhance accessibility to quantitative movement assessment; and virtual labs improve conceptual understanding, learner independence, and blended learning. However, measurement accuracy issues, infrastructure disparities, data governance concerns, and limited teacher expertise in digital biomechanics continue to limit adoption. The unique contribution of this article is its integration of biomechanics, AI, and digital pedagogy into a comprehensive educational framework, rather than treating them as separate technical trends. The review concludes that biomechanical analysis technologies can significantly boost motor learning, assessment quality, and curriculum relevance when combined with teacher training, pedagogically sound implementation, and equitable institutional support. These findings offer a practical roadmap for modernizing PE into an inclusive, evidence-based, and forward-looking field.

Keywords: Biomechanical analysis Markerless Motion analysis Physical education Virtual laboratories

How to Cite

Biomechanical Analysis Technologies in Physical Education: A Systematic Review of Motion Analysis, Markerless AI, and Virtual Laboratories. (2026). PACE: Journal of Sport Education Research, 1(1), 50-69. https://doi.org/10.65508/j25mv428

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