EEG-based Brain-Computer Interface to support post-stroke motor rehabilitation of the upper limb

Area of Science:

• Neuroscience
• Rehabilitation Medicine
• Biomedical Engineering

Background:

• Brain-Computer Interfaces (BCIs) enable real-time processing of brain activity for non-muscular interaction.
• Motor Imagery (MI) is a cognitive process quantifiable by BCIs, useful in rehabilitation.
• Stroke recovery often involves challenges in patient engagement and monitoring during therapy.

Purpose of the Study:

• To propose and evaluate a BCI-based rehabilitation device for promoting motor recovery after stroke.
• To assess the device's utility as a monitoring tool for physical therapists.
• To investigate the impact of BCI-mediated neurofeedback on patient engagement and neuroplasticity.

Main Methods:

• A BCI-based rehabilitation device was developed and tested in a hospital setting with 29 stroke patients.
• Eight patients underwent a one-month training program using the device as an adjunct to standard therapy.
• An enhanced system incorporating Electromyographic (EMG) analysis and Functional Electrical Stimulation (FES) is under evaluation.

Main Results:

• BCI-mediated neurofeedback demonstrated enhanced engagement of motor areas compared to Motor Imagery alone.
• The device facilitated patient participation in cognitive rehabilitative exercises.
• Preliminary findings suggest potential improvement in functional outcomes for motor rehabilitation.

Conclusions:

• BCI-based neurofeedback can promote neuroplasticity in stroke-affected brain regions.
• The developed BCI device shows promise in improving patient engagement and potentially enhancing motor rehabilitation outcomes.
• Further clinical evaluation, including systems with EMG and FES, is ongoing.