Low back pain (LBP) is a pervasive global health challenge, affecting approximately 80% of adults and frequently progressing into chronic or recurrent episodes. While exercise therapy is a primary clinical intervention, traditional at-home programs suffer from low adherence rates and the absence of professional supervision. This study introduces TOSHFA, an accessible mobile VR-based rehabilitation system that bridges this gap by combining computer vision with affordable hardware. The system utilizes a laptop webcam to perform real-time pose estimation via the MediaPipe framework, tracking 33 skeletal landmarks to provide immediate biofeedback. This data is streamed via low-latency UDP protocols to a smartphone mounted in a cardboard-style VR headset, where patients interact with a gamified 3D environment. A pilot study with 20 participants evaluated the system’s performance and user engagement. Quantitative results yielded a mean System Usability Scale (SUS) score of 47.4, indicating marginal usability and a need for interface optimization. However, Game Experience Questionnaire (GEQ) data revealed high scores in positive affect and enjoyment, suggesting that the gamification elements–such as coin rewards and streak tracking–successfully maintained user motivation despite technical friction. These findings validate the feasibility of a smartphone-based tele-rehabilitation model and establish a technical foundation for future clinical trials involving multi-exercise protocols.

生成讲解博客的中文版本

生成AI智能校验的中文版本