SEDA-EEG: A semi-supervised emotion recognition network with domain adaptation for cross-subject EEG analysis

• Published in: Neurocomputing (Amsterdam) Vol. 622; p. 129315
• Main Authors: Tan, Weilong, Zhang, Hongyi, Wang, Yingbei, Wen, Weimin, Chen, Liang, Li, Han, Gao, Xingen, Zeng, Nianyin
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 14.03.2025
• Subjects: Brain-computer interface (BCI); Cross-subject; Domain adaption; Offline feature decomposition; Offline feature decomposition; Brain-computer interface (BCI); Cross-subject; Domain adaption

In this paper, a cross-subject emotion recognition network based on semi-supervised and domain adversarial learning with electroencephalogram (EEG) signals (SEDA-EEG) is proposed, which addresses the challenge of high EEG variability from different subjects in brain-computer interface (BCI) research...