Unsupervised domain adaptation techniques based on auto-encoder for non-stationary EEG-based emotion recognition

• Published in: Computers in biology and medicine Vol. 79; pp. 205 - 214
• Main Authors: Chai, Xin, Wang, Qisong, Zhao, Yongping, Liu, Xin, Bai, Ou, Li, Yongqiang
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.12.2016; Elsevier Limited
• Subjects: Adult; Algorithms; Auto-encoder; Classification; Databases, Factual; Domain adaptation; EEG; Electroencephalography; Electroencephalography - methods; Emotion recognition; Emotions - drug effects; Emotions - physiology; Female; Humans; Internal Medicine; Male; Methods; MMD; Other; Signal Processing, Computer-Assisted; Studies; Support Vector Machine; Young Adult; Domain adaptation; Emotion recognition; Auto-encoder; MMD; EEG

In electroencephalography (EEG)-based emotion recognition systems, the distribution between the training samples and the testing samples may be mismatched if they are sampled from different experimental sessions or subjects because of user fatigue, different electrode placements, varying impedances,...