The Application of Entropy in Motor Imagery Paradigms of Brain–Computer Interfaces

<b>Background:</b> In motor imagery brain–computer interface (MI-BCI) research, electroencephalogram (EEG) signals are complex and nonlinear. This complexity and nonlinearity render signal processing and classification challenging when employing traditional linear methods. Information en...

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Bibliographic Details
Published in:Brain Sciences
Main Authors: Chengzhen Wu, Bo Yao, Xin Zhang, Ting Li, Jinhai Wang, Jiangbo Pu
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Subjects:
information entropy
motor imagery
electroencephalogram
pattern classification
Online Access:https://www.mdpi.com/2076-3425/15/2/168

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https://www.mdpi.com/2076-3425/15/2/168

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