Emotion Recognition and EEG Analysis Using ADMM-Based Sparse Group Lasso

This study presents an efficient sparse learning-based pattern recognition framework to recognize the discrete states of three emotions-happy, angry, and neutral emotion-using electroencephalogram (EEG) signals. In affective computing with massive spatiotemporal brainwave signals, a large number of...

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Veröffentlicht in:	IEEE transactions on affective computing 2022-01, Vol.13 (1), p.199-210
Hauptverfasser:	Puk, Kin Ming, Wang, Shouyi, Rosenberger, Jay, Gandy, Kellen C., Harris, Haley Nicole, Peng, Yuan Bo, Nordberg, Anne, Lehmann, Peter, Tommerdahl, Jodi, Chiao, Jung-Chih
Format:	Artikel
Sprache:	eng
Schlagworte:	Affective computing Algorithms Atmospheric measurements Brain Brain modeling Classification EEG electroencephalogram Electroencephalography Emotion recognition Emotions Feature extraction feature selection group structure learning Learning Medical imaging multi-modal emotion processing Multivariate analysis Pattern recognition Physiology supervised learning
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