Motor Imagery-Based Brain-Computer Interface Combined with Multimodal Feedback to Promote Upper Limb Motor Function...

Area of Science:

• Neuroscience
• Rehabilitation Medicine
• Biomedical Engineering

Background:

• Stroke frequently causes severe upper limb and hand motor impairments.
• Brain-computer interfaces (BCIs) are emerging as a potential tool for motor function recovery in chronic stroke patients.

Purpose of the Study:

• To investigate the efficacy of motor imagery (MI)-based BCI training with multimodal feedback for improving motor function in chronic stroke patients.
• To compare the effects of BCI training with classical motor imagery training.

Main Methods:

• A randomized controlled trial involving 12 chronic stroke patients with severe upper limb/hand motor impairment.
• Participants were assigned to either MI-based BCI training with multimodal feedback or classical MI training.
• Evaluations included motor function assessments (FMA-UE, ARAT, MSS, BI) and electrophysiological measures (EEG) before and after intervention.

Main Results:

• The BCI group showed a significant improvement in Fugl-Meyer Assessment-Upper Extremity (FMA-UE) scores compared to baseline (p=0.006).
• Motor Status Scale (MSS) scores improved in both groups; Action Research Arm Test (ARAT) did not significantly improve.
• Four patients regained wrist extension ability post-intervention, with two in each group.

Conclusions:

• Motor imagery-based BCI training, enhanced with sensory and visual feedback, may offer benefits for severe upper limb and hand impairments in chronic stroke.
• This BCI approach demonstrates potential for application in stroke rehabilitation medicine.