Dual selections based knowledge transfer learning for cross-subject motor imagery EEG classification

Dual selections based knowledge transfer learning for cross-subject motor imagery EEG classification

IntroductionMotor imagery electroencephalograph (MI-EEG) has attracted great attention in constructing non-invasive brain-computer interfaces (BCIs) due to its low-cost and convenience. However, only a few MI-EEG classification methods have been recently been applied to BCIs, mainly because they suf...

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Bibliographic Details
Main Author: Tian-jian Luo
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-11-01
Series:Frontiers in Neuroscience
Subjects:
motor imagery
electroencephalograph
cross-subject
feature selection
domain adaptation
noninvasive brain computer interface
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2023.1274320/full

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https://www.frontiersin.org/articles/10.3389/fnins.2023.1274320/full

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