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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https://www.mdpi.com/2306-5354/10/2/186

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