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Updated: Sep 10, 2025
Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
Published on: September 1, 2023
Multimodal assessment of a BCI system for stroke rehabilitation integrating motor imagery and motor attempts: a
Juan He1,2, Ziwen Yuan1,3,2, Lu Quan1,2
1Department of Rehabilitation, First Affiliated Hospital of Xi'an Jiaotong University, No. 277 Yanta West Road, Xi'an, 710061, Shaanxi, China.
Background:
Brain-computer interface (BCI) technology based on motor imagery (MI) or motor attempt (MA) has shown promise in enhancing motor function recovery in stroke patients. This study aimed to evaluate the effectiveness of BCI-based rehabilitation in improving motor function through multimodal assessment, and to explore the potential neuroplastic changes resulting from this intervention.
Methods:
We conducted a randomized double-blind controlled clinical trial with multimodal assessment to evaluate the efficacy of a BCI system for enhancing motor recovery. A total of 48 ischemic stroke patients completed the study (25 BCI, 23 control). The BCI group used an 8-electrode electroencephalogram (EEG) system, a virtual reality training module, and a rehabilitation training robot for real-time motor intention-based feedback. The control group used identical BCI devices but without displaying real-time data and feedback. Participants underwent 20-minute upper and lower limb training sessions for two weeks. Motor function (Fugl-Meyer Extremity scale), electromyography (EMG), and functional near-infrared spectroscopy (fNIRS) were assessed pre- and post-intervention.
Results:
The BCI group demonstrated significantly greater improvement in upper extremity motor function compared to the control group (ΔFMA-UE: 4.0 vs. 2.0, p = 0.046). EEG results of the BCI group showed a significant decrease in both DAR (p = 0.031) and DABR (p < 0.001) compared to baseline. EMG analysis revealed that BCI treatment resulted in significant increases in deltoid and bicipital muscle activity during both shoulder and elbow flexion movements compared to baseline (p < 0.01). fNIRS results indicated enhanced functional connectivity and activation in key motor-related brain regions, including the prefrontal cortex, supplementary motor area, and primary motor cortex in the BCI group.
Conclusion:
BCI-based rehabilitation using an attention-motor dual-task paradigm significantly improved upper limb motor function and enhanced motor and cognitive network activity in stroke patients. Multimodal assessment supports the potential of BCI rehabilitation as an effective tool for leveraging neuroplasticity and promoting motor recovery.
