A Novel Deep Learning Model for Motor Imagery Classification in Brain–Computer Interfaces

A Novel Deep Learning Model for Motor Imagery Classification in Brain–Computer Interfaces

Recent advancements in decoding electroencephalogram (EEG) signals for motor imagery tasks have shown significant potential. However, the intricate time–frequency dynamics and inter-channel redundancy of EEG signals remain key challenges, often limiting the effectiveness of single-scale feature extr...

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Bibliographic Details
Main Authors: Wenhui Chen, Shunwu Xu, Qingqing Hu, Yiran Peng, Hong Zhang, Jian Zhang, Zhaowen Chen
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Information
Subjects:
EEG signals
brain–computer interfaces
deep learning
Online Access:https://www.mdpi.com/2078-2489/16/7/582
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