An EEG-based subject-independent emotion recognition model using a differential-evolution-based feature selection algorithm

• Published in: Knowledge and information systems Vol. 65; no. 1; pp. 341 - 377
• Main Authors: Kannadasan, K., Veerasingam, Sridevi, Shameedha Begum, B., Ramasubramanian, N.
• Format: Journal Article
• Language: English
• Published: London Springer London 01.01.2023; Springer Nature B.V
• Subjects: Algorithms; Arousal; Classification; Computer Science; Computing time; Data Mining and Knowledge Discovery; Database Management; Electroencephalography; Emotion recognition; Emotional factors; Emotions; Evolution; Feature extraction; Feature selection; Information Storage and Retrieval; Information Systems and Communication Service; Information Systems Applications (incl.Internet); IT in Business; Optimization; Performance degradation; Performance enhancement; Regular Paper; Support vector machines; Swarm optimization; Differential evolution; Emotion recognition; Feature selection; Electroencephalogram

Electroencephalogram (EEG)-based emotion recognition models are gaining interest as they show the intrinsic state of human. A wide range of features are extracted from the scalp EEG recorded using a different set of electrodes across the brain regions. However, there are no standard set of features...