Development of Emotional Decision-Making Model Using EEG Signals

In this paper, an attempt has been made to explore the effect of incidental emotion on decision making. For this, first of all, a conventional emotion classification system based on electroencephalogram (EEG) signal is implemented. This emotion classification system ensures the generation and presence of four basic emotions, happy, relaxing, sad and angry by stimulations. audio-visual stimulations are used to generate specific emotions. The novelty of this work is in analysis of pre- and post-decisions taken with respect to stimulation provided. For this, answers of same question were taken before and after the induced emotions by stimulation. After observation and analysis, maximum (46.67%) percentage of change in decision has been noticed during angry emotion.