A Deep Learning Approach for Brain Computer Interaction-Motor Execution EEG Signal Classification

A Deep Learning Approach for Brain Computer Interaction-Motor Execution EEG Signal Classification

Recently Noninvasive Electroencephalogram (EEG) systems are gaining much attention. Brain-computer Interface (BCI) systems rely on EEG analysis to identify the mental state of the user, change in cognitive state and response to the events. Motor Execution (ME) is a very important control paradigm. T...

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Bibliographic Details
Main Authors: Nesma E. Elsayed, Ahmed S. Tolba, Magdi Z. Rashad, Tamer Belal, Shahenda Sarhan
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Deep neural networks
independent component analysis
machine learning
motor execution
Online Access:https://ieeexplore.ieee.org/document/9488193/

Internet

https://ieeexplore.ieee.org/document/9488193/

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