Brain-computer interfaces (BCIs) represent an innovative approach to neurorehabilitation for neurological conditions, particularly stroke, multiple sclerosis, and Parkinson’s disease. This paper provides a comprehensive analysis of current BCI applications, technological developments, and clinical outcomes in these conditions. Recent advances in electroencephalography-based BCIs have demonstrated promising results, with classification accuracies exceeding 90% in stroke rehabilitation and comparable performance in multiple sclerosis and Parkinson’s disease. Meta-analyses of stroke rehabilitation trials (n=235) indicate significant motor function improvements, with standardized mean differences of 0.79 in upper limb assessment scores compared to conventional therapy. Disease-specific challenges necessitate tailored approaches, while hybrid systems combining multiple signal types and integration with virtual reality or robotic assistance enhance therapeutic potential. The development of portable, home-based systems offers increased therapy intensity but raises concerns about remote monitoring and safety protocols. This review synthesizes current evidence supporting BCI applications in neurorehabilitation and highlights critical areas for future research, including cognitive rehabilitation optimization and the standardization of outcome measures for cross-condition comparison.

 

brain-computer interface, neurorehabilitation, stroke, multiple sclerosis, Parkinson’s disease, motor imagery, neuroplasticity

 

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