Multisource Transfer Learning for Cross-Subject EEG Emotion Recognition

• Published in: IEEE transactions on cybernetics Vol. 50; no. 7; pp. 3281 - 3293
• Main Authors: Li, Jinpeng, Qiu, Shuang, Shen, Yuan-Yuan, Liu, Cheng-Lin, He, Huiguang
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adult; Brain - physiology; Brain modeling; Brain-Computer Interfaces; Brain–computer interface; Calibration; Data models; Electroencephalography; Electroencephalography - classification; Electroencephalography - methods; Emotion recognition; Emotions; Emotions - classification; Humans; Learning; Machine Learning; Mapping; Pattern Recognition, Automated - methods; Temporal resolution; Training; Training data; transfer learning (TL); Young Adult

Electroencephalogram (EEG) has been widely used in emotion recognition due to its high temporal resolution and reliability. Since the individual differences of EEG are large, the emotion recognition models could not be shared across persons, and we need to collect new labeled data to train personal...