Adaptive deep feature representation learning for cross-subject EEG decoding

The promising results highlight the effectiveness of the ADFR algorithm for EEG decoding and show its potential for practical applications.

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Publication Details

Journal
BMC Bioinformatics
Published
2024-12-31
DOI
https://doi.org/10.1186/s12859-024-06024-w
Citations
7
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
2.40

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article

Adaptive deep feature representation learning for cross-subject EEG decoding

Wei Feng, Linzhe Li, Wei Zu, Wenlong Hang et al.
7 citations
BMC Bioinformatics
EEG and Brain-Computer Interfaces
2.40
article

Adaptive deep feature representation learning for cross-subject EEG decoding

Wei Feng, Linzhe Li, Wei Zu, Wenlong Hang, Shuang Liang
article en
7 citations

Abstract

The promising results highlight the effectiveness of the ADFR algorithm for EEG decoding and show its potential for practical applications.

BMC BioinformaticsVol. 25(1)
Nanjing Tech University (CN), Nanjing University of Posts and Telecommunications (CN), Monash University (AU)
National Natural Science Foundation of China, Government of Jiangsu Province, Natural Science Research of Jiangsu Higher Education Institutions of China
Openalex Percentile: Top 11%
EEG and Brain-Computer Interfaces
2.40
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