Multi-Modal Domain Adaptation Variational Autoencoder for EEG-Based Emotion Recognition

• Published in: IEEE/CAA journal of automatica sinica Vol. 9; no. 9; pp. 1612 - 1626
• Main Authors: Wang, Yixin, Qiu, Shuang, Li, Dan, Du, Changde, Lu, Bao-Liang, He, Huiguang
• Format: Journal Article
• Language: English
• Published: Piscataway Chinese Association of Automation (CAA) 01.09.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Brain modeling; Calibration; Cycle-consistency; Data models; domain adaptation; Domains; electroencephalograph (EEG); Electroencephalography; Emotion recognition; Emotions; Human-computer interface; Image reconstruction; Knowledge management; Modal data; multi modality; Regularization; Representations; variational autoencoder

Traditional electroencephalograph (EEG)-based emotion 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...