Topological EEG Nonlinear Dynamics Analysis for Emotion Recognition

Topological EEG Nonlinear Dynamics Analysis for Emotion Recognition

Emotional recognition through exploring the electroencephalography (EEG) characteristics has been widely performed in recent studies. Nonlinear analysis and feature extraction methods for understanding the complex dynamical phenomena are associated with the EEG patterns of different emotions. The ph...

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Bibliographic Details
Main Authors: He, Y. (Author), Li, A. (Author), Li, C. (Author), Li, H. (Author), Wang, L. (Author), Wu, X. (Author), Yan, Y. (Author), Zhang, Z. (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
affective computing
Affective Computing
Biomedical signal processing
biomedical signal processing.
Biomedical signal processing.
Biomedical signals processing
Brain modeling
Data analysis
Data handling
dynamical systems
Dynamical systems
Dynamics
EEG emotion recognition
Electroencephalography
Electrophysiology
Emotion recognition
Exploring the electroencephalography emotion recognition
Extraction
Feature extraction
Features extraction
Information analysis
Nonlinear analysis
Nonlinear dynamical systems
nonlinear dynamics
phase space reconstruction
Phase space reconstruction
Phase spaces
Point cloud compression
Point-clouds
Signal analysis
Space reconstruction
Speech recognition
Time series analysis
topological data analysis
Topological data analysis
Topology
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