Multi-Classifier Fusion Based on MI–SFFS for Cross-Subject Emotion Recognition

• Published in: Entropy (Basel, Switzerland) Vol. 24; no. 5; p. 705
• Main Authors: Yang, Haihui, Huang, Shiguo, Guo, Shengwei, Sun, Guobing
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 16.05.2022; MDPI
• Subjects: Accuracy; Affective computing; Algorithms; Artificial intelligence; Asymmetry; Brain research; Channels; Classification; Classifiers; cross-subject; Datasets; Discriminant analysis; Electroencephalography; Emotion recognition; Emotions; Entropy; Experiments; Feature extraction; Information theory; Machine learning; Multi-Classifier Fusion; mutual information; Physiology; Researchers; SFFS; Splicing; Support vector machines; Multi-Classifier Fusion; mutual information; cross-subject; emotion recognition; SFFS

With the widespread use of emotion recognition, cross-subject emotion recognition based on EEG signals has become a hot topic in affective computing. Electroencephalography (EEG) can be used to detect the brain’s electrical activity associated with different emotions. The aim of this research is to...