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Updated: May 6, 2026
Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
Published on: September 1, 2023
Hybrid BCI for upper limb rehabilitation: integrating MI with peripheral field SSVEP stimulation
Ruoqing Zhang1, Zhaohui Li1, Xiaohu Pan2
1State Key Laboratory of Advanced Medical Materials and Devices, Institute of Biomedical Engineering, Tianjin Institutes of Health Science, Chinese Academy of Medical Science and Peking Union Medical College, Tianjin, China; Tianjin Key Laboratory of Neuromodulation and Neurorepair, Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China.
Background:
Rehabilitation systems based on brain-computer interfaces (BCIs) hold significant potential for stroke patients. Existing systems, predominantly relying on motor imagery (MI), have room for improvement in both performance and user comfort. This study aims to enhance these aspects by developing a hybrid BCI system integrating MI with steady-state visual evoked potentials (SSVEPs) elicited by peripheral visual field stimulation.
New Methods:
The system is coupled with a soft robotic hand for feedback, forming a closed-loop framework. The design incorporates concentric rings with 7° and 10° eccentricities as peripheral stimuli, flashing at frequencies of 34 Hz and 35 Hz for left and right sides, respectively, to evoke SSVEPs. A central video (304 ×304 pixels) of left-hand/right-hand grasping motions guides subjects in performing synchronized MI tasks simply by focusing on it, which could also complete the SSVEP task.
Results:
The offline results of 11 subjects showed that the classification result of MI was 70.65 ± 3.38 %, and the SSVEP result was 96.04 ± 3.33 %, and the fusion result reached 96.23 ± 3.21 %, which confirmed the validity of the fusion method. The online experiment of 11 subjects achieved a result of 97.12 ± 2.09 %, validating the feasibility of the system.
Comparison With Existing Methods:
The proposed system improves the comfort level while ensuring the performance of the system as compared to the existing systems.
Conclusion:
The feasibility of the proposed system was verified by offline and online experiments to advance the clinical applications.
