# Exploring neural activity changes during motor imagery-based brain-computer interface training with robotic hand for upper limb rehabilitation in ischemic stroke patients: a pilot study

## TL;DR

This pilot study explores how brain-computer interface training with a robotic hand helps stroke patients regain upper limb function and identifies changes in brain activity during the process.

## Contribution

The study introduces a novel pilot approach combining motor imagery-based BCI with robotic hand assistance for stroke rehabilitation and identifies individual neural activity patterns.

## Key findings

- Significant improvements in motor function were observed in all participants.
- EEG analysis showed high-alpha band ERD at motor cortex locations with individual variability in frequency and power.
- No consistent neural activity trends were found across training sessions.

## Abstract

This pilot study aimed to evaluate the feasibility and tolerability of motor imagery (MI)-based brain-computer interface (BCI) training with robotic hand assistance for upper limb rehabilitation, and to explore preliminary neural markers in ischemic stroke patients.

Three post-stroke participants performed MI tasks combined with exoskeleton-assisted movements to facilitate rehabilitation training. Electroencephalography (EEG) signals were recorded to assess the neural correlates of MI. Functional outcomes were evaluated using standard assessment tools.

Our results demonstrated significant improvements in motor function across all participants. Additionally, EEG analysis revealed event-related desynchronization (ERD) in the high-alpha band power at motor cortex locations, with individual differences in both the frequency and power of neural activity. However, no significant trends in neural activity were observed across the training sessions.

These findings suggest that MI-based BCI training, combined with robotic assistance, offer a promising approach for enhancing upper limb function in ischemic stroke patients.