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Objective Motion Tracking for Rehabilitation: Quantitative Assessment Using Pose Estimation

Kok Swee Sim, Mahda Laina Arnumukti

International Journal on Advanced Science, Engineering and Information Technology · 2026

Vollständiger Abstract

Worum geht es in dieser Arbeit?

Evaluation of the effectiveness of rehabilitation therapy is often based on patient outcomes and functional improvement over time. However, traditional approaches are subjective and heavily influenced by expert perspectives and perceptions, which can lead to inconsistencies in research. This study developed a motion measurement system that improves body positioning by using computer vision techniques to quantitatively assess elbow flexibility and range of motion during rehabilitation. The system uses a novel posture estimation model that analyses video input to identify key body points and match body position, providing smooth, real-time feedback. In addition, the system is designed to be easy to use and simple, so it can be implemented in both clinical settings and home-based rehabilitation programs. Data validation is carried out using a reference dataset that has previously been analyzed, with an absolute mean error of approximately 5.00 degrees and a correlation coefficient of approximately 0.95. The results show that this system can be used to maintain one's own behavior. This technology supports the rehabilitation process by providing clear data, helping medical professionals and health care providers better assess patient progress and make more appropriate decisions. In addition, this technology can improve tele-rehabilitation services, especially for patients who cannot access medical facilities. With that in mind, limitations such as model issues and video quality variations can affect the accuracy of body-position determination.

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Publikationsdaten

Autor:innen
Kok Swee Sim, Mahda Laina Arnumukti
Quelle
International Journal on Advanced Science, Engineering and Information Technology
Publikation
2026-01-01
Band / Ausgabe
Nicht angegeben
Seiten
Nicht angegeben
ISSN / ISBN
2460-6952, 2088-5334
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Zitierfähiger Nachweis

Kok Swee Sim, Mahda Laina Arnumukti (2026). Objective Motion Tracking for Rehabilitation: Quantitative Assessment Using Pose Estimation. International Journal on Advanced Science, Engineering and Information Technology. https://doi.org/10.18517/ijaseit.16.4.22012
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