ROMBandAR: Development of an AR-Based Wrist ROM Assessment Prototype for Rehabilitation

Wrist range of motion (ROM) assessment is important in rehabilitation because wrist movement supports hand positioning and functional hand use. Limited wrist movement can be caused by a variety of conditions, including neurological conditions such as stroke and musculoskeletal or orthopedic injuries such as distal radius fractures or tendon repairs. In current practice, wrist ROM is commonly assessed using a goniometer. Although the tool is widely used, the reading still depends on correct positioning, therapist handling, and visual judgment. Augmented reality has the potential to support this process because it can show digital feedback together with the real wrist movement. However, AR is still not widely explored for wrist-specific ROM assessment compared with virtual reality, robotics, and wearable or sensor-based systems. This study presents the development of ROMBandAR, an AR-based wrist ROM assessment prototype for rehabilitation. The prototype uses a wrist armband as a model target for AR tracking. The armband was first scanned using KIRI Engine software, then trained using Vuforia Model Target Generator, and lastly imported into Unity for AR integration. MediaPipeUnityPlugin was also integrated to show hand landmarks on the detected hand via the smartphone camera. After that, custom C# scripts were developed to display wrist ROM readings, classify movement, show real-time feedback, save assessment readings, and support report submission for therapist review. This study follows the Design Science Research Methodology and, at this stage, focuses on development-level testing. Three test cases were carried out: device compatibility testing, application functionality testing, and screenshot-based ROM reading consistency testing. The results show that ROMBandAR can run on different Android devices, successfully detect the wrist armband, display hand landmarks, show ROM readings, and save assessment results. These findings provide an early foundation for future evaluation of the proposed framework, especially the extrinsic feedback provided during wrist ROM assessment. Repeated trials, inter-rater reliability, direct goniometer measurement of the wrist, and further evaluation of the feedback were not part of this development stage and are planned as future work.

@article{Johan2026,
  title     = {ROMBandAR: Development of an AR-Based Wrist ROM Assessment Prototype for Rehabilitation},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {17},
  number    = {8},
  year      = {2026},
  publisher = {The Science and Information Organization},
  author    = {Nurul Aimi Johan and Wan Rizhan and Normala Rahim},
  doi       = {10.14569/IJACSA.2026.0170815},
  url       = {https://doi.org/10.14569/IJACSA.2026.0170815}
}