Temporal shift residual network for EEG-based emotion recognition: A 3D feature image sequence approach

• Published in: Multimedia tools and applications Vol. 83; no. 15; pp. 45739 - 45759
• Main Authors: Chen, Yu, Zhang, Haopeng, Long, Jun, Xie, Yining
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.05.2024; Springer Nature B.V
• Subjects: Accuracy; Arousal; Computer Communication Networks; Computer Science; Data exchange; Data Structures and Information Theory; Electroencephalography; Emotion recognition; Emotions; Feature maps; Image sequencing; Modelling; Modules; Multimedia Information Systems; Representations; Special Purpose and Application-Based Systems; Track 2: Medical Applications of Multimedia; emotion recognition; EEG; robust representation; DEAP

In EEG-based emotion recognition, finding EEG representations that maintain both temporal and spatial features is crucial. This study aims to identify robust representations from EEG independent of subject differences and discriminative. We convert EEG data into feature image sequences with 3D repre...