This thesis explores the integration of virtual reality (VR) and electroencephalography (EEG) for post-stroke motor rehabilitation through a proof-of-concept study of a VR-EEG upper limb rehabilitation platform. Stroke remains a leading cause of disability in adults, often resulting in significant upper limb impairments that hinder daily activities and reduce quality of life. As the need for motor rehabilitation increases, new technologies are being developed to meet the demand for individualized and accessible care. The VR application used in the study provides a 3D environment for rehabilitative training with functional tasks that mirror everyday activities. It records comprehensive performance data, including hand trajectories, and integrates EEG recording. The application was tested with four healthy individuals over multiple training sessions and showed significant training effects on task completion times, but not on movement quality. Changes in performance coincided with decreases in EEG sensorimotor activity, indicating motor learning. Participants found the setup comfortable in terms of cybersickness symptoms, but only moderately engaging. The thesis concludes with an evaluation indicating that the application has potential to support motor learning and provide comprehensive monitoring data, but needs software improvements to promote natural motor behavior and user engagement. The implications of the findings for the design of VR-BCI systems based on principles of motor learning and neuroplasticity are discussed.
|
