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Emotions Detection Through the Analysis of Physiological Information During Video Games Fruition

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Games and Learning Alliance (GALA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10653))

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Abstract

Games are interactive tools able to arouse emotions in the user. This is particularly relevant in Serious Games, where the main goal could be educational, pedagogical, etc. Therefore, understanding the players’ emotions during the game fruition could provide a valid support to the developers and researchers in video games field in order to design a more effective product. The presented research is a starting point to propose a framework for the determination of the player emotions through physiological information. We acquire several signals: facial electromyography, electrocardiogram, galvanic skin response, and respiration rate. We then compare the data to an emotional player assessment, defined using a valence and an arousal vector, through the application of Machine Learning techniques. The obtained results seem to suggest that the proposed approach can represent a valid tool to analyze the players’ emotions.

The original version of this article was revised. Modifications have made to Fig. 2. For detailed information please see erratum. The erratum to this publication is available online at https://doi.org/10.1007/978-3-319-71940-5_23

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Authors and Affiliations

  1. Department of Computer Science, University of Milan, via Comelico 39, 20135, Milan, Italy

    Marco Granato, Davide Gadia, Dario Maggiorini & Laura Anna Ripamonti

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  1. Marco Granato
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  2. Davide Gadia
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  3. Dario Maggiorini
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  4. Laura Anna Ripamonti
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Corresponding author

Correspondence to Marco Granato .

Editor information

Editors and Affiliations

  1. University of Lisbon, Lisbon, Portugal

    João Dias

  2. University of Lisbon, Lisbon, Portugal

    Pedro A. Santos

  3. Utrecht University, Utrecht, The Netherlands

    Remco C. Veltkamp

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Granato, M., Gadia, D., Maggiorini, D., Ripamonti, L.A. (2017). Emotions Detection Through the Analysis of Physiological Information During Video Games Fruition. In: Dias, J., Santos, P., Veltkamp, R. (eds) Games and Learning Alliance. GALA 2017. Lecture Notes in Computer Science(), vol 10653. Springer, Cham. https://doi.org/10.1007/978-3-319-71940-5_18

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  • DOI: https://doi.org/10.1007/978-3-319-71940-5_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71939-9

  • Online ISBN: 978-3-319-71940-5

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