Cross-Subject EEG Feature Selection for Emotion Recognition Using Transfer Recursive Feature Elimination

• Published in: Frontiers in neurorobotics Vol. 11; p. 19
• Main Authors: Yin, Zhong, Wang, Yongxiong, Liu, Li, Zhang, Wei, Zhang, Jianhua
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 10.04.2017; Frontiers Media S.A
• Subjects: Arousal; Classification; Collaboration; Computer applications; EEG; Electroencephalography; Emotions; Learning algorithms; Neuroscience; Physiology; Spectrum analysis; Statistical analysis; Workloads; China; recursive feature elimination; physiological signals; affective computing; emotion recognition; EEG

Using machine-learning methodologies to analyze EEG signals becomes increasingly attractive for recognizing human emotions because of the objectivity of physiological data and the capability of the learning principles on modeling emotion classifiers from heterogeneous features. However, the conventi...