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Emotion Prediction through EEG Recordings Using Computational Intelligence
Journal
Computational Intelligence for Information Retrieval
Date Issued
2021-01-01
Author(s)
Hasan, Asif
Khan, Azizuddin
Parveen, Asma
Nair, Rajit
Abstract
Nowadays, the affective computing community is focusing on extracting emotional states using electroencephalography (EEG). Numerous experiments have been published of similar methods, using computational intelligence techniques to classify the subjects’ emotions. Features derived from the EEG were used as an input for the computational intelligence method. This chapter will represent the computational intelligence method for machine learning for predicting emotions by using EEG. The EEG and physiological data provide a lot more than previous research, and we have used a new public 257-channel EEG data for the analysis of valence (positive or negative emotions). The chapter will activate brain areas by applying source localization techniques. We compare the performance of the extracted features with valence classification, showing that the source reconstruction improves the classifier results. We looked at the effects on the classifications.