Multi-Modal Domain Adaptation Variational Auto-encoder for EEG-Based Emotion Recognition

• Published in: 自动化学报（英文版） Vol. 9; no. 9; pp. 1612 - 1626
• Main Authors: Yixin Wang, Shuang Qiu, Dan Li, Changde Du, Bao-Liang Lu, Huiguang He
• Format: Journal Article
• Language: English
• Published: Research Center for Brain-inspired Intelligence,National Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Science,Beijing 100190 01.09.2022; University of Chinese Academy of Sciences,Beijing 100049%Research Center for Brain-inspired Intelligence,National Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Science,Beijing 100190; Beijing Institute of Control and Electronic Technology,Beijing 100038,China%Research Center for Brain-inspired Intelligence,National Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Science,Beijing 100190; Center for Excellence in Brain Science and Intelligence Technology,Chinese Academy of Science,Beijing,China; University of Chinese Academy of Sciences,Beijing 100049; School of Mathematics and Information Sciences,Yantai University,Yantai 264003,China%Department of Computer Science and Engineering,Shanghai Jiao Tong University,Shanghai 200240,China%Research Center for Brain-inspired Intelligence,National Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Science,Beijing 100190
• Subjects: Cycle-consistency; multi modality; electroence-phalograph(EEG); domain adaptation; variational autoencoder

Traditional electroencephalograph(EEG)-based emo-tion recognition requires a large number of calibration samples to build a model for a specific subject,which restricts the application of the affective brain computer interface(BCI)in practice.We attempt to use the multi-modal data from the past sess...