Gusa: Graph-Based Unsupervised Subdomain Adaptation for Cross-Subject EEG Emotion Recognition

• Published in: IEEE transactions on affective computing Vol. 15; no. 3; pp. 1451 - 1462
• Main Authors: Li, Xiaojun, Chen, C. L. Philip, Chen, Bianna, Zhang, Tong
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation; Adaptation models; Brain modeling; Constraints; Convolution; EEG emotion recognition; Electroencephalography; Emotion recognition; Emotions; graph convolutional neural network; Measurement; metric learning; Modules; Representations; subdomain adaptation; Task analysis
• ISSN: 1949-3045; 1949-3045
• DOI: 10.1109/TAFFC.2024.3349770

EEG emotion recognition has been hampered by the clear individual differences in the electroencephalogram (EEG). Nowadays, domain adaptation is a good way to deal with this issue because it aligns the distribution of data across subjects. However, the performance for EEG emotion recognition is limit...