Fusing Frequency-Domain Features and Brain Connectivity Features for Cross-Subject Emotion Recognition

• Published in: IEEE transactions on instrumentation and measurement Vol. 71; pp. 1 - 15
• Main Authors: Chen, Chuangquan, Li, Zhencheng, Wan, Feng, Xu, Leicai, Bezerianos, Anastasios, Wang, Hongtao
• Format: Journal Article
• Language: English
• Published: New York IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Affective computing; Approximate empirical kernel map (AEKM); Brain; brain connectivity (BC) features; Channels; cross-subject emotion recognition; Datasets; Electroencephalography; Emotion recognition; Emotional factors; Emotions; Feature extraction; Frequencies; Frequency domain analysis; frequency-domain (FD) features; fused features; Human-computer interface; Kernel; Motion pictures; Support vector machines

Frequency-domain (FD) features reveal the activated patterns of individual local brain regions responding to different emotions, whereas brain connectivity (BC) features involve the coordination of multiple brain regions for generating emotional responses; these two types of features are complementa...