| Next-Gen Stroke Recovery: Harnessing BCIs, VR, FES, and Robotics for Neurorehabilitation: A Systematic Review |
| Paper ID : 1095-ISCSR3 (R1) |
| Authors |
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Moustafa A. Gouda *1, Anas M. Qamar2, Ali Alhassan Ali3 1faculty of Physical Therapy, Pharos University, Alexandria, Egypt 2Faculty of physical therapy, pharos University, Alexandria, Egypt 3Faculty of Physical therapy, pharos university, Alexandria, Egypt |
| Abstract |
| Background: Stroke typically results in irreversible motor deficits, which demand advanced neurorehabilitation techniques. Brain-Computer Interfaces (BCIs) offer a novel approach by providing neural control of external devices. The combination of BCIs with Virtual Reality (VR), Functional Electrical Stimulation (FES), and Robotics can induce motor function recovery through providing greater neuroplasticity than unimodal therapies. The effectiveness and difficulties of these different BCI techniques (BCI+VR/FES/Robotics) haven't been thoroughly compared in the current literature. Objectives: To systematically review the effectiveness of EEG-based BCI systems combined with VR, FES, or robotics to improve upper limb motor function (e.g., motor control scale) in post-stroke patients. Furthermore, the objective analysis is to highlight technological trends, neuroplastic mechanisms, user engagement variables, and current implementation challenges related to these integrated systems. Design of the study: Systematic literature review. Methods: We systematically searched PubMed, Scopus, and Web of Science for published studies from the last 10 years. Designs included (RCTs, reviews, pilot/case studies, technical descriptions) that compared EEG-BCI combined with VR, FES, or robotics for upper limb rehabilitation in adults following stroke. Data regarding interventions, outcomes (e.g., FMA), and results were extracted, and the methodological quality of included studies was taken into account throughout synthesis. Results: The analysis of 42 included papers (descriptive reports, systemic reviews, and intervention trials) showed consistent support for the efficacy of BCI. BCI+FES showed strong motor function gains (FMA scores) in stroke phases. BCI+VR promoted increased user engagement, while BCI+Robotics provided adaptive physical assistance. Functional gains were often associated with neuroplastic changes. Major challenges are BCI control variability, system complexity/cost/usability, fatigue, and lack of standardization. Conclusion: Hybrid BCI therapies (VR/FES/Robotics) are very promising for stroke recovery through neuroplasticity, with BCI+FES being particularly effective. Future research demands larger trials, standardization, better BCI accessibility/adaptability, solutions for user variability solutions, and evaluation of clinical translation and cost. |
| Keywords |
| Keywords Brain-Computer Interface, Stroke Rehabilitation, Virtual Reality, Functional Electrical Stimulation, Robotics |
| Status: Abstract Accepted |