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Current status and future prospects of brain–computer interfaces in the field of neurological disease rehabilitation

脑-机接口 背景(考古学) 肌萎缩侧索硬化 医学 物理医学与康复 范围(计算机科学) 康复 保证 接口(物质) 神经科学 神经康复 疾病 转化研究 多发性硬化 辅助技术 脊髓损伤 领域(数学) 脑病 心理学 本体感觉 评论文章 系统回顾 计算机科学
作者
Yu Luo,Xiaohu Liu,Miaomiao Yang
出处
期刊:Frontiers in rehabilitation sciences [Frontiers Media SA]
卷期号:7: 1666530-1666530
标识
DOI:10.3389/fresc.2026.1666530
摘要

Neurological disorders represent a significant category of diseases that profoundly affect human health, accounting for the second leading cause of global mortality. This group of conditions includes stroke, multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), spinal cord injury, Parkinson's disease, and cerebral palsy, among others. These disorders are highly susceptible to sequelae and profoundly impact individuals' daily lives. In this context, Brain-Computer Interface (BCI) technology has demonstrated considerable potential in the domain of neurorehabilitation, although numerous challenges remain. The manuscript provides a comprehensive review of recent advancements in research and clinical applications, highlighting current limitations and outlining future directions. It elucidates the applicability and constraints of Brain-Computer Interface (BCI) technology across various diseases and patient populations. To facilitate insights across different conditions, comparative tables are presented, aligning BCI strategies with therapeutic targets, outcomes, advantages, limitations, and existing evidence gaps. The scope extends beyond motor restoration to include under-explored domains, such as neuropathic pain, with a focus on real-world translation, including home and community feasibility and the distinction between assistive and rehabilitative applications. The review distills overarching limitations within the field, such as small sample sizes, protocol heterogeneity, and limited longitudinal evidence, while synthesizing the most recent studies. An actionable research and development roadmap is proposed to guide next-generation BCI rehabilitation, incorporating individualized cortical-network simulators, self-architecting decoders, adaptive therapy approaches akin to game seasons, and proprioceptive "write-back" mechanisms via peripheral interfaces. Moreover, the review reveals significant research focal points and critical issues that warrant further investigation in the context of neurological rehabilitation utilizing BCI technology.
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