Statistically significant features improve binary and multiple Motor Imagery task predictions from EEGs

Statistically significant features improve binary and multiple Motor Imagery task predictions from EEGs

In recent studies, in the field of Brain-Computer Interface (BCI), researchers have focused on Motor Imagery tasks. Motor Imagery-based electroencephalogram (EEG) signals provide the interaction and communication between the paralyzed patients and the outside world for moving and controlling externa...

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Bibliographic Details
Main Authors: Murside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Yalcin Isler
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-07-01
Series:Frontiers in Human Neuroscience
Subjects:
brain-computer interfaces (BCIs)
electroencephalogram (EEG)
feature selection
machine learning
Motor Imagery (MI) task classification
Online Access:https://www.frontiersin.org/articles/10.3389/fnhum.2023.1223307/full

Internet

https://www.frontiersin.org/articles/10.3389/fnhum.2023.1223307/full

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