数据采集与处理2026，Vol.41Issue(4)：910-945,36.DOI:10.16337/j.1004-9037.2026.04.002
基于脑电信号的脑机接口智能解码技术及临床应用
Brain Computer Interface Intelligent Decoding Technology Based on EEG Signal and Its Clinical Application
摘要
Abstract
Brain-computer interface(BCI)establishes information pathways between the human brain and external devices by analyzing brain activity,providing new technical means for assisted communication,functional assessment,rehabilitation training,and neuromodulation.Electroencephalography(EEG)is one of the most widely used signal modalities in non-invasive BCI and brain health research because of its non-invasiveness,low cost,high temporal resolution,and ease of repeated acquisition.Driven by recent advances in artificial intelligence,EEG decoding has expanded from conventional control command recognition to complex brain-state representation,visual and linguistic semantic reconstruction,and real-time closed-loop interaction;accordingly,this paper reviews representative progress in control intent decoding,brain-state decoding,high-level semantic decoding,general representation learning,and closed-loop interaction,and analyzes their applications in stroke rehabilitation,language and visual function rehabilitation,epilepsy detection and early warning,assessment of disorders of consciousness,and auxiliary diagnosis of mental disorders.Although the representational capacity and application scope of EEG decoding continue to expand,clinical maturity varies markedly across different directions:control intent recognition,abnormal-state detection,and closed-loop neurorehabilitation have accumulated a certain research foundation,whereas visual and linguistic semantic decoding remains largely limited to healthy participants and controlled experimental settings;major barriers to clinical translation include cross-individual and cross-center generalization,neural information fidelity,long-term stability,incremental clinical value,closed-loop safety,and ethical regulation.Future research should be guided by real clinical needs and patient outcomes to advance intelligent EEG decoding from methodological feasibility toward stable,reliable,and evaluable clinical applications.关键词
脑机接口/脑电信号/智能解码/脑状态评估/脑健康/临床应用Key words
brain-computer interface(BCI)/EEG signals/intelligent decoding/brain state assessment/brain health/clinical application分类
信息技术与安全科学引用本文复制引用
郑炜豪,杜亚峰,付钰,张喆..基于脑电信号的脑机接口智能解码技术及临床应用[J].数据采集与处理,2026,41(4):910-945,36.基金项目
国家重大科研仪器研制项目(62227807). National Major Scientific Instruments and Equipments Development Project(No.62227807). （62227807）
