Continual Learning of a Transformer-Based Deep Learning Classifier Using an Initial Model from Action Observation EEG Data to Online Motor Imagery Classification

Continual Learning of a Transformer-Based Deep Learning Classifier Using an Initial Model from Action Observation EEG Data to Online Motor Imagery Classification

The motor imagery (MI)-based brain computer interface (BCI) is an intuitive interface that enables users to communicate with external environments through their minds. However, current MI-BCI systems ask naïve subjects to perform unfamiliar MI tasks with simple textual instruction or a visual/audito...

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Bibliographic Details
Main Authors:	Po-Lei Lee, Sheng-Hao Chen, Tzu-Chien Chang, Wei-Kung Lee, Hao-Teng Hsu, Hsiao-Huang Chang
Format:	Article
Language:	English
Published:	MDPI AG 2023-02-01
Series:	Bioengineering
Subjects:	brain computer interface electroencephalography (EEG) action observation motor imagery transformer network
Online Access:	https://www.mdpi.com/2306-5354/10/2/186

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