Virtual Reality Rehabilitation Training System Based on Multimodal Brain-computer Interface

Authors

Jing Qu, School of Software, Shandong University, Jinan 250101, China; Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan 250101, China
Kaining Fang, School of Software, Shandong University, Jinan 250101, China; Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan 250101, China
Shantong Zhu, School of Animation and Digital Arts, Communication University of China, Beijing 100024, China
Lingguo Bu, School of Software, Shandong University, Jinan 250101, China; Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan 250101, China

Abstract

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.

Recommended Citation

Qu, Jing; Fang, Kaining; Zhu, Shantong; and Bu, Lingguo (2026) "Virtual Reality Rehabilitation Training System Based on Multimodal Brain-computer Interface," Journal of System Simulation: Vol. 38: Iss. 1, Article 10.
DOI: 10.16182/j.issn1004731x.joss.25-0836
Available at: https://dc-china-simulation.researchcommons.org/journal/vol38/iss1/10

First Page

125

Last Page

135

CLC

TP391.9; TN911.7

Recommended Citation

Qu Jing, Fang Kaining, Zhu Shantong, et al. Virtual Reality Rehabilitation Training System Based on Multimodal Brain-computer Interface[J]. Journal of System Simulation, 2026, 38(1): 125-135.

Corresponding Author

Bu Lingguo

DOI

10.16182/j.issn1004731x.joss.25-0836