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Development of Emotional Decision-Making Model Using EEG Signals

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1176))

Abstract

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.

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References

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Acknowledgements

This research and study are done under a project entitled “Development of Computational Model for Decision Making based on Emotion Recognition through EEG signal” in file no. ECR/2017/000250, funded by SCIENCE & ENGINEERING RESEARCH BOARD (SERB) a statutory body of the Department of Science & Technology, government of India.

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We have taken permission from competent authorities to use the images/data as given in the paper. In case of any dispute in the future, we shall be wholly responsible.

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Correspondence to Mitul Kumar Ahirwal .

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Ahirwal, M.K., Kose, M.R. (2021). Development of Emotional Decision-Making Model Using EEG Signals. In: Bhateja, V., Peng, SL., Satapathy, S.C., Zhang, YD. (eds) Evolution in Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1176. Springer, Singapore. https://doi.org/10.1007/978-981-15-5788-0_27

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