Cross-Subject and Cross-Session EEG Emotion Recognition based on Multi-Source Structural Deep Clustering

• Published in: IEEE transactions on cognitive and developmental systems pp. 1 - 15
• Main Authors: Chen, Yiyuan, Xu, Xiaodong, Qin, Xiaowei
• Format: Journal Article
• Language: English
• Published: IEEE 24.02.2025
• Subjects: Brain modeling; Convolutional neural networks; Cross-Session; Cross-Subject; Data mining; EEG Emotion Recognition; Electroencephalography; Emotion recognition; Feature extraction; Long short term memory; Multi-Source; Nearest neighbor methods; Structural Deep Clustering; Support vector machines; Training

Individual fluctuations and temporal variabilities of Electroencephalogram (EEG) pose challenges in precisely identifying emotions. Although a model performs well with data specific to a certain subject or session, the fluctuations in EEG data can significantly impair the performance on a different...