A Marker Free Visual-based Home Rehabilitation Framework

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Roy Kwang Yang Chang
Kok Swee Sim
Siong Hoe Lau


Adhesive capsulitis or more commonly known as frozen shoulder, is a familiar occurrence for adults aged above 40 caused by the inflammation of the connective tissues surrounding the shoulder joint. There are different severity of adhesive capsulitis but patients afflicted with frozen shoulder typically will experience stiffness, severe pain, and reduced range of motion (ROM) for the shoulder. No matter the course of treatment being non-steroidal anti-inflammatory drugs (NSAIDs) or steroid injections, which can help reduce the inflammation and reduce pain, in order to restore ROM for the afflicted shoulder joint, rehabilitation exercises need to be performed. Even without the current climate where medical workers are severely overworked, physical therapists are in short order especially for developing countries like Malaysia. A remedy for this situation would be to deploy home rehabilitation instead. This would be a way for patients to get proper rehabilitation exercises in between visits to the clinic to meet the physical therapist. This can also reduce the frequency of in-clinic visits while still allowing the patient to progress in the rehabilitation of their afflicted shoulder joint. Though home rehabilitation seems like a clear solution, it does come with its own set of challenges. How open will the patients themselves be to utilizing a home rehabilitation system? In light of that, this paper proposes a home rehabilitation framework focusing on a marker free visual-based implementation using the Microsoft Kinect camera. The framework will measure the impact of variables such as capability, motivation and opportunity on the adoption rate of the home rehabilitation. Cronbach’s Alpha tests were conducted to ascertain the reliability of the variables used in the framework.

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How to Cite
Chang, R. K. Y., Sim, K. S., & Lau, S. H. (2023). A Marker Free Visual-based Home Rehabilitation Framework. Journal of Informatics and Web Engineering, 2(2), 122–128. https://doi.org/10.33093/jiwe.2023.2.2.9