Real-world clinical characteristics of motor disorders for personalised brain-computer interfaces: phenotypic insights from a specialised clinic

Motor dysfunction caused by neurological disorders such as stroke, spinal cord injury and amyotrophic lateral sclerosis has become a major global public health issue. Conventional rehabilitation approaches yield limited efficacy, highlighting the urgent need for innovative therapies. Brain-computer interface (BCI) technology offers a promising avenue for motor function restoration by decoding motor intentions and driving external devices or providing sensory feedback. However, current BCI development has predominantly emphasised technical performance metrics, lacking systematic investigation into the clinical characteristics of real-world patient populations. This disconnect between technological advancement and genuine clinical demands persists because existing studies often recruit idealised subjects while neglecting prevalent conditions like stroke and lack standardised assessments of clinically meaningful outcomes. Consequently, system designs frequently fail to align with patient-specific profiles. To address this gap, our study established a prospective BCI evaluation outpatient cohort, comprehensively collecting data from patients presenting with motor dysfunction throughout 2025. Among the total of 1641 patients with motor dysfunction, the majority were patients with chronic-phase stroke (1087, 66.24%). The cohort was primarily middle-aged, with a mean age of 45.93±11.23 years. The study further detailed patterns of muscle strength, joint range of motion and sensory impairments. The goal is to construct the first clinical profile characteristics to inform precise patient selection and guide personalised system design.