Application of Brain-Computer Interface in Post-Stroke Disease Rehabilitations

Stroke is one of the leading causes of long-term disabling illness in the world, resulting in persistent functional impairment in 75% of survivors. Traditional rehabilitation methods are often limited by their inability to effectively activate long-term neuroplasticity. This study investigated the use of brain-computer interface (BCI) technology in post-stroke rehabilitation and systematically assessed its clinical efficacy for limb function recovery by analyzing neural signal decoding mechanisms and classification (invasive/non-invasive). The results of this paper showed that a motor imagery (MI)-based BCI training program enhanced neural coupling between the motor cortex and the affected limb, reflecting clinical significance in hand grasp, joint range of motion, and motor coordination. For comorbid upper and lower extremity dysfunction, the BCI intervention yielded across-the-board benefits: walking speed improved by 0.15 m/s, spasticity scores (wrists, fingers, and ankles) were significantly reduced, and Barthel Index (BI) scores improved by 5.0 points. These synchronized improvements confirm the synergistic effect of BCI on motor function, spasticity control and activities of daily living. The integrated BCI robotic system incorporates Error-Related Negativity (ERN) decoding, enabling real-time detection of motor intent errors (8.5:1 detection-to-false-alarm ratio) and precise millisecond adjustment of assistive forces. This technological advancement permits early initiation of active neuroplasticity training in acute phase patients with complete loss of voluntary movement, confirming superior efficacy compared to conventional therapy alone. By facilitating active neural remodeling, BCI technology overcomes the limitations of passive rehabilitation and offers transformative potential for chronic patients.