Global Adaptive Transformer for Cross-Subject Enhanced EEG Classification

Global Adaptive Transformer for Cross-Subject Enhanced EEG Classification

Due to the individual difference, EEG signals from other subjects (source) can hardly be used to decode the mental intentions of the target subject. Although transfer learning methods have shown promising results, they still suffer from poor feature representation or neglect long-range dependencies....

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Bibliographic Details
Main Authors: Yonghao Song, Qingqing Zheng, Qiong Wang, Xiaorong Gao, Pheng-Ann Heng
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
EEG classification
domain adaptation
transformer
brain-computer interface (BCI)
motor imagery
Online Access:https://ieeexplore.ieee.org/document/10149036/

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