Computer-mediated rehabilitation tools require a high degree of motor control and are therefore inadequate for patients with significant impairment in motor control. Consequently, many stroke survivors are unable to benefit. The REHABNET (REHABNET: Neuroscience based interactive systems for motor rehabilitation) project came up with an innovative approach to address this critical need. Researchers successfully developed a hybrid brain-computer interface (BCI)-virtual reality (VR) system that assesses user capability and dynamically adjusts its difficulty level. This motor imagery-based BCI system is tailored to meet the needs of patients using a VR environment for game training coupled with neurofeedback through multimodal sensing technologies. The game training scenarios address both cognitive and motor abilities. The four rehabilitation scenarios include bimanual motor training, dual motor cognitive-motor training and a simulated city for training on daily living activities. Pilot and longitudinal studies demonstrated the benefits of longitudinal VR training as compared to existing rehabilitation regimens. The self-report questionnaires also revealed a high user acceptance of the novel system. Designed for at-home use, the REHABNET toolset is platform-independent and freely available globally as an app (Reh@Mote). Besides deeper insight on factors affecting stroke recovery, this could aid in further improvement of rehabilitation strategies. More importantly, these low-cost toolsets could also address the needs of patients with severe motor and cognitive deficits. Efforts are ongoing to facilitate future commercial exploitation through a technology transfer agreement.
Stroke rehabilitation, motor control, REHABNET, brain-computer interface, virtual reality