Abstract:

The aging population has led to an increasing demand for rehabilitation for cognitive and motor functions. In response to the lack of interest in traditional rehabilitation and the absence of objective physiological assessment in existing virtual reality (VR) rehabilitation systems, a VR rehabilitation training system based on multimodal brain computer interface is developed by integrating VR interaction, near-infrared brain functional imaging, and motion capture technology. An immersive cognitive-motor integrated training environment was constructed to guide users in completing upper limb tasks. By recruiting subjects and synchronously collecting brain network data and Kinect upper limb motion parameters, multimodal assessment was performed. The results show that VR training can enhance the efficiency of the prefrontal network. Furthermore, during the tasks, the elderly group exhibited a stronger neural connections compensation mechanism, whereas the young group demonstrated higher motor efficiency. The proposed method enables objective quantitative assessment of rehabilitation, providing a novel multimodal assessment paradigm for VR rehabilitation and offering significant guidance for the age-friendly design of rehabilitation systems.

Key words: virtual reality(VR), brain-computer interface, functional near-infrared spectroscopy, upper-limb rehabilitation, multimodal assessment, cognitive training