BCI for Hemiparetic Upper Extremities in Patients Due to Stroke

Non-invasive brain-computer interface (BCI) technology is one of the new training approaches to achieve motor restoration through a closed-loop system from brain activity through event-related desynchronization (ERD) after motor imagery (MI) or movement attempt to peripheral feedback triggered by an external hepatic device. Often, it is unclear whether the BCI intervention itself or the assistance of the external device leads to neural responses and functional gains. This study adopts a closed-loop BCI system involving ERD induced by MI. Functional electrical stimulation (FES) and virtual reality (VR) are simultaneously delivered as feedback. The aim is to investigate the efficacy of closed-loop BCI training combined with FES and VR on the recovery of the hemiparetic upper extremity of individuals with chronic stroke. Chronic stroke survivors are being recruited and randomly allocated into 3 groups: (1) BCI-FES-VR - participants look at an external screen displaying the VR avatar participant's arms while performing wrist dorsiflexion MI in random order (left or right). The BCI system detects the ERD of the motor area corresponding to correct MI. Then, visual feedback with the VR and motor-tactile feedback with the discharge of the FES is delivered; (2) BCI-FES - same procedure as group 1, but the difference is that the participant's hands replace the VR system; (3) BCI-VR - same procedure as group 1, but the FES is removed. Each session requires 240 MI trials with a training duration of 10 sessions in a 3-week interval. Motor and MI assessments are being conducted at post-assessment and at a 3-week follow-up. The findings of this study will provide significant new information regarding neurophysiological motor relearning mechanisms, which could inform the development and evaluation of BCI-based treatment for individuals with stroke and impact the field of translational neuroscience.