On the Development of EEG based Emotion Classification

This paper proposes an investigation on classification of the positive and negative emotions via the use of electroencephalogram (EEG). EEG bandpowers are extracted as the feature of interest. Two simple decision rules to classify positive and negative emotions are proposed, i.e. 1) using both the left and right frontal information and 2) using only one side of the left or right frontal information. First decision reports low accuracy while the second decision rule can achieve higher accuracy between 80 to 90%. This can be concluded that the proposed method is possible for the real-time emotion classification in neuroeconomics.