Emotion Recognition Using a Reduced Set of EEG Channels Based on Holographic Feature Maps

Emotion Recognition Using a Reduced Set of EEG Channels Based on Holographic Feature Maps

An important function of the construction of the Brain-Computer Interface (BCI) device is the development of a model that is able to recognize emotions from electroencephalogram (EEG) signals. Research in this area is very challenging because the EEG signal is non-stationary, non-linear, and contain...

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Bibliographic Details
Main Authors: Russo, M. (Author), Saric, M. (Author), Stella, M. (Author), Topic, A. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Biomedical signal processing
Brain computer interface
Brain-Computer Interface
Computer generated holography
computer-generated holography
Computer-generated holography
Convolutional neural networks
deep learning
Deep learning
Electrodes
electroencephalogram
Electroencephalogram signals
Electroencephalography
Emotion recognition
Extraction
Feature extraction
Feature map
gender specific emotion recognition
Gender specific emotion recognition
Neighborhood component analysis
Neighborhood Component Analysis
Reduced sets
ReliefF
Speech recognition
valence-arousal-dominance model
Valence-arousal-dominance model
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