Abstract
Brain-computer interfaces (BCIs) — systems that establish direct communication pathways between the brain and external devices by recording and decoding neural signals — represent a rapidly maturing technology with transformative potential for neurorehabilitation following stroke, spinal cord injury, and neurodegenerative disease. BCIs enable patients with severe motor impairments to control external devices — robotic orthoses, communication systems, functional electrical stimulation devices — through decoded neural intent, bypassing damaged motor pathways and potentially driving neuroplastic recovery through contingent sensorimotor feedback. This review evaluates 44 studies of BCI applications in neurorehabilitation published between 2015 and 2024, analysing system types, clinical populations, rehabilitation outcomes, and implementation requirements. EEG-based BCIs remain the most clinically accessible technology, with motor imagery-based systems demonstrating improvements in upper limb function of 15–35% on validated outcome measures in stroke rehabilitation randomised controlled trials. Implantable electrocorticographic and Utah array BCIs have achieved milestone demonstrations of restored communication and motor control in paralysed individuals. Implementation barriers including cost, training burden, and signal reliability are evaluated in the context of neurology and rehabilitation services in Uzbekistan.
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