运动想象脑机接口解码算法研究综述

doi:10.12267/j.issn.2096-5931.2026.06.002

摘要/Abstract

摘要：

运动想象脑机接口(Motor Imagery Brain-Computer Interface,MI-BCI)是一种通过采集大脑的脑电信号进行预处理、特征提取和分类,从而实现脑神经与外部设备信息交互的技术。运动想象作为脑机接口的核心范式之一,在医疗康复、文娱等领域有着广泛的应用前景。系统梳理了MI-BCI领域的相关技术内容,重点聚焦于机器学习和深度学习在MI-BCI领域中的解码算法研究,并探究未来MI-BCI领域的研究方向与应用。

关键词: 脑机接口, 运动想象, 解码算法, 机器学习, 深度学习

Abstract:

Motor Imagery Brain-Computer Interfaces (MI-BCI) are technologies that enable information exchange between the brain and external devices by acquiring electroencephalographic (EEG) signals from the brain and performing preprocessing, feature extraction, and classification. As one of the core paradigms of BCI, motor imagery holds broad application prospects in fields such as medical rehabilitation and entertainment. This paper systematically reviews the relevant technical development in the MI-BCI field, with a particular focus on decoding algorithms based on machine learning and deep learning. Furthermore, it explores future research directions and potential applications of MI-BCI.

Key words: BCI, motor imagery, decoding algorithm, machine learning, deep learning

中图分类号:

TP391.4
R318

黄鑫, 梁栗炎, 张倩. 运动想象脑机接口解码算法研究综述[J]. 信息通信技术与政策, 2026, 52(6): 9-17.

HUANG Xin, LIANG Liyan, ZHANG Qian. A review of decoding algorithms for MI-BCI[J]. Information and Communications Technology and Policy, 2026, 52(6): 9-17.

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链接本文:

http://ictp.caict.ac.cn/CN/10.12267/j.issn.2096-5931.2026.06.002

http://ictp.caict.ac.cn/CN/Y2026/V52/I6/9

图/表 1

参考文献 34

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