Advancing Trunk Control and Balance in Rehabilitation: A Quantitative Approach Using VR Head-Mounted Display and Motion-Sensing Technologies (Preprint)

BACKGROUND Virtual reality (VR) technology is increasingly vital across sectors like healthcare, engineering, and science, with applications in training, education, clinical evaluations, and rehabilitation. In rehabilitation, it is instrumental for assessing and treating various conditions, particularly for enhancing balance and gait in patients with neurological impairments, and offers added benefits when integrated with conventional therapies. However, current VR systems lack methods and technologies for the functional quantification of training performance. OBJECTIVE This study aims to address the gap of the absence of methods and technologies for the functional quantification of training performance in current VR systems. METHODS The study employs VR head-mounted displays and motion-sensing recognition technologies, which are integrated to facilitate precise positioning and free movement within a VR environment, leveraging motion interaction functions to target trunk control and balance training. It also introduces a functional quantification framework encompassing algorithms for analyzing movement trajectories, trunk activity, and three-dimensional spatial motion performance. RESULTS The functional quantification framework digitally records and updates participants' rehabilitation journeys in real-time, generating functional reports. CONCLUSIONS These functional reports enable medical professionals and patients to continuously monitor rehabilitation progress, thereby enhancing the overall efficacy of the treatment process.