Abstract
This paper describes elementary experiments for a technique to estimate the emotion of a user from the biological signals of user’s central nervous system, such as cerebral blood flow and brain wave. The proposed technique uses multiple regression analysis in providing a high resolution measure to the emotional valence, which could not be realized with the existing methods based on peripheral nervous system. To demonstrate the effectiveness of the proposed emotion estimation technique in emotion based interaction, we also implemented an emotional painting tool that dynamically adapts the colors of brush and the outline of canvas to the estimated emotion of the user by recording biological signals and analyzing them in real time. The tool allows users to create original images that reflect their emotion.
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Omata, M., Kanuka, D., Mao, X. (2014). Experiments for Emotion Estimation from Biological Signals and Its Application. In: Gavrilova, M.L., Tan, C.J.K., Mao, X., Hong, L. (eds) Transactions on Computational Science XXIII. Lecture Notes in Computer Science, vol 8490. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43790-2_10
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DOI: https://doi.org/10.1007/978-3-662-43790-2_10
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