SMMTM: Motor imagery EEG decoding algorithm using a hybrid multi-branch separable convolutional self-attention temporal convolutional network

Motor imagery (MI) is a brain-computer interface (BCI) technology with the potential to change human life in the future. MI signals have been widely applied in various BCI applications, including neurorehabilitation, smart home control, and prosthetic control. However, the limited accuracy of MI sig...

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Bibliographic Details
Published in:	PloS one Vol. 20; no. 10; p. e0333805
Main Authors:	Cao, DianGuo, Yu, ZhenYuan, Wang, Jinqiang, Wu, Yuqiang
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 23.10.2025 Public Library of Science (PLoS)
Subjects:	Accuracy Algorithms Analysis Biochips Brain Brain research Brain-Computer Interfaces Classification Computational linguistics Computer applications Convolution Datasets Decoding Deep learning Electroencephalography - methods Human-computer interface Humans Imagery Imagination - physiology Implants Language processing Mental task performance Natural language interfaces Neural networks Neural Networks, Computer Neurology Prostheses Rehabilitation Smart buildings Technology application Temporal variations China
ISSN:	1932-6203, 1932-6203
Online Access:	Get full text
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