Abstract
In this paper, we explore the possibility of using the visual and sound stimuli obtained in various incidents when immersed in virtual reality, to detect human emotion by measuring the human bio-signals: heart rate, electroencephalogram (EEG), blood volume pressure, skin temperature and galvanic skin response (GSR) using bio-sensors. Further classification of signals occurs using a neural network. The received statistical characteristics are used as a contribution to the neural network for classification according to the Lövheim cube of emotions. The resulting algorithm for recognizing emotions based on human bio-signals in virtual reality will be used to predict emotional reactions to various events in virtual environments and, consequently, to increase their immersion.
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Acknowledgment
This work was funded by the subsidy of the Russian Government to support the Program of competitive growth of Kazan Federal University among world class academic centers and universities.
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Kugurakova, V., Ayazgulova, K. (2019). Neurotransmitters Level Detection Based on Human Bio-Signals, Measured in Virtual Environments. In: Samsonovich, A. (eds) Biologically Inspired Cognitive Architectures 2018. BICA 2018. Advances in Intelligent Systems and Computing, vol 848. Springer, Cham. https://doi.org/10.1007/978-3-319-99316-4_28
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DOI: https://doi.org/10.1007/978-3-319-99316-4_28
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