EEG channel selection based on sequential backward floating search for motor imagery classification

EEG channel selection based on sequential backward floating search for motor imagery classification

Brain-computer interfaces (BCIs) based on motor imagery (MI) utilizing multi-channel electroencephalogram (EEG) data are commonly used to improve motor function of people with motor disabilities. EEG channel selection can enhance MI classification accuracy by selecting informative channels, accordin...

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Bibliographic Details
Main Authors: Chao Tang, Tianyi Gao, Yuanhao Li, Badong Chen
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-10-01
Series:Frontiers in Neuroscience
Subjects:
electroencephalogram (EEG)
channel selection
sequential backward floating search (SBFS)
motor imagery (MI)
brain-computer interface (BCI)
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2022.1045851/full

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https://www.frontiersin.org/articles/10.3389/fnins.2022.1045851/full

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