Domain-Invariant Adaptive Graph Regularized Label Propagation for EEG-Based Emotion Recognition

• Published in: IEEE access Vol. 12; pp. 126774 - 126792
• Main Authors: Tao, Jianwen, Yan, Liangda, He, Tao
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation; Adaptation models; adaptive graph Laplacian; Brain modeling; Data models; domain adaptation; EEG emotion recognition; Electroencephalography; Emotion recognition; Emotions; Feature recognition; Invariants; Knowledge management; Knowledge representation; label propagation; Labels; Machine learning; maximum mean discrepancy; Optimization; Propagation; Signal classification; Transfer learning

Emotion recognition holds significant potential for various real-world applications due to its reliability and precision. Nevertheless, variations in EEG patterns among individuals restrict the ability of emotion classifiers to generalize across different people. Furthermore, the non-stationary natu...