Enhanced Online Continuous Brain-Control by Deep Learning-Based EEG Decoding

This study suggests the good utility of deep learning in MI-BCIs and has implications for clinical applications such as stroke rehabilitation.

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Publication Details

Journal
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Published
2025-01-01
DOI
https://doi.org/10.1109/tnsre.2025.3591254
Citations
4
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
5.72
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article

Enhanced Online Continuous Brain-Control by Deep Learning-Based EEG Decoding

Lin Yao, Yueming Wang, Jiaheng Wang
4 citations
IEEE Transactions on Neural Systems and Rehabilitation Engineering
EEG and Brain-Computer Interfaces
5.72
article

Enhanced Online Continuous Brain-Control by Deep Learning-Based EEG Decoding

Lin Yao, Yueming Wang, Jiaheng Wang
article en
4 citations

Abstract

This study suggests the good utility of deep learning in MI-BCIs and has implications for clinical applications such as stroke rehabilitation.

IEEE Transactions on Neural Systems and Rehabilitation EngineeringVol. 33
Zhejiang Lab (CN), Zhejiang University (CN)
Openalex Percentile: Top 4%
EEG and Brain-Computer Interfaces
5.72
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