EISATC-Fusion: Inception Self-Attention Temporal Convolutional Network Fusion for Motor Imagery EEG Decoding

EISATC-Fusion: Inception Self-Attention Temporal Convolutional Network Fusion for Motor Imagery EEG Decoding

The motor imagery brain-computer interface (MI-BCI) based on electroencephalography (EEG) is a widely used human-machine interface paradigm. However, due to the non-stationarity and individual differences among subjects in EEG signals, the decoding accuracy is limited, affecting the application of t...

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Bibliographic Details
Main Authors: Guangjin Liang, Dianguo Cao, Jinqiang Wang, Zhongcai Zhang, Yuqiang Wu
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
Brain–computer interface (BCI)
motor imagery (MI)
attention collapse
temporal convolution network (TCN)
transfer learning
Online Access:https://ieeexplore.ieee.org/document/10480732/

Internet

https://ieeexplore.ieee.org/document/10480732/

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