ADFCNN: Attention-Based Dual-Scale Fusion Convolutional Neural Network for Motor Imagery Brain–Computer Interface

ADFCNN: Attention-Based Dual-Scale Fusion Convolutional Neural Network for Motor Imagery Brain–Computer Interface

Convolutional neural networks (CNNs) have been successfully applied to motor imagery (MI)-based brain–computer interface (BCI). Nevertheless, single-scale CNN fail to extract abundant information over a wide spectrum from EEG signals, while typical multi-scale CNNs cannot effectively fuse...

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Bibliographic Details
Main Authors: Wei Tao, Ze Wang, Chi Man Wong, Ziyu Jia, Chang Li, Xun Chen, C. L. Philip Chen, Feng Wan
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
Convolutional neural networks (CNNs)
motor imagery (MI)
brain–computer interface (BCI)
self-attention mechanism
Online Access:https://ieeexplore.ieee.org/document/10356088/

Internet

https://ieeexplore.ieee.org/document/10356088/

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