Classification of EEG signals for facial expression and motor execution with deep learning

Volume: 19, Issue: 5, Pages: 1588 - 1593
Published: Oct 1, 2021
Abstract
Recently, algorithms of machine learning are widely used with the field of electroencephalography (EEG) brain-computer interfaces (BCI). The preprocessing stage for the EEG signals is performed by applying the principle component analysis (PCA) algorithm to extract the important features and reducing the data redundancy. A model for classifying EEG, time series, signals for facial expression and some motor execution processes had been designed....
Paper Details
Title
Classification of EEG signals for facial expression and motor execution with deep learning
Published Date
Oct 1, 2021
Volume
19
Issue
5
Pages
1588 - 1593
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