Recognition and analyses of EEG & ERP signals related to emotion: from the perspective of psychology

Abstract

Electroencephalography (EEG) is widely used to record activities of human brain in the area of psychology for many years. With the development of technology, neural basis of functional areas of emotion processing is revealed gradually. In order to extract the useful information of emotion from the background of EEG signals and noise, we propose to combine methods of psychology and the technology of signal processing such as pattern recognition, etc. In this paper, we first review the psychological methods and signal processing technology in the field of emotion research, and point out the junctions of these two approaches. Secondly, we introduce a method to evaluate emotion competence objectively, which involves the analyses of frequency fluctuations of EEG signals and frontal EEG asymmetry. Then, we take an example of event-related potentials (ERP) study about the face recognition task and the discrimination of sad/happy/neutral emotional facial expressions task. Finally, we indicate the present difficulties in this research area, and advance the possible solution to resolve these problems.