| Title |
Development of Kinect-Based Proprioception Evaluation and Classification System |
| Authors |
윤주원(Joowon Yun) ; 김은빈(Eunbin Kim) ; 이언석(Onseok Lee) |
| DOI |
https://doi.org/10.5370/KIEE.2025.74.8.1373 |
| Keywords |
Proprioception; Kinect; Unity; Decision Tree; Random Forest; Paired T-test; Skeleton Point; Rehabilitation |
| Abstract |
Proprioception is the fundamental sense that enables the central nervous system to process body positions, postures, and movements in functional tasks. Aging and neurological disorders often lead to proprioceptive impairments that affect balance and coordination. This study developed a contactless system using Kinect and Unity 3D to evaluate proprioception by quantifying joint angles under visual and positional restrictions. Participants performed specific postures with proprioceptive limitations induced by 2 kg weights and closed-eye conditions. Paired t tests revealed significant proprioceptive variations under these constraints. Random forest achieved a classification accuracy of 96%, effectively distinguishing sensory changes across conditions. These results highlight the potential of this system for rehabilitation and training programs targeting proprioceptive function. |