A review of decoding algorithms for MI-BCI

doi:10.12267/j.issn.2096-5931.2026.06.002

Abstract

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

CLC Number:

TP391.4
R318

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

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

Figures/Tables 1

References 34

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