Electrical, Hemodynamic, and Motor Activity in BCI Post-stroke Rehabilitation: Clinical Case Study

Area of Science:

• Neuroscience
• Rehabilitation Medicine
• Biomedical Engineering

Background:

• Stroke recovery assessment often relies on clinical scales, potentially missing nuanced neural changes.
• Brain-computer interfaces (BCIs) offer novel ways to assess and facilitate motor recovery.
• Integrated analysis of multimodal data (EEG, fMRI, motor activity) can provide a comprehensive view of neurorehabilitation.

Observation:

• A post-stroke patient with extensive cortical lesion underwent neurorehabilitation using a hand exoskeleton controlled by a BCI based on kinesthetic motor imagery.
• Clinical data, including Fugl-Meyer scale and biomechanical analysis, were collected over three hospitalizations.
• Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) were used to analyze brain activity during motor imagery.

Findings:

• EEG analysis revealed distinct patterns in intact brain areas and identified task-specific activity near the lesion edge with altered mu-rhythm.
• These EEG signal characteristics served as biomarkers for the BCI.
• fMRI showed a reduction in activated areas for paretic hand imagery and an increase for intact hand imagery, indicating motor recovery.

Implications:

• Integrated analysis of EEG, fMRI, and motor activity provides a comprehensive assessment of motor system reorganization post-stroke.
• This multimodal approach enhances the evaluation of BCI-assisted exoskeleton rehabilitation efficacy.
• Findings suggest potential for improved personalized rehabilitation strategies based on neural biomarkers.