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http://dx.doi.org/10.7583/JKGS.2017.17.6.29

First-Person Shooter Player Analysis System Based on Biometrics  

Kim, Dong-Gyun (School of Games, Hongik University)
Bae, Byung-Chull (School of Games, Hongik University)
Kang, Shin-Jin (School of Games, Hongik University)
Publication Information
Journal of Korea Game Society / v.17, no.6, 2017 , pp. 29-38 More about this Journal
Abstract
Predicting the user's reaction to the game at the stage of developing the game is important because it is related to the popularity of the game. In this paper, we propose a system that can collect and analyze game user's biometric information in a non-invasive way. To this end, we developed a mouse with skin conductance, pressure, gyroscope, and accelerometer sensor using Arduino. In order to verify the usefulness of this system, the subject was experimented with playing the first person shooter game with this mouse. We analyzed the gameplay videos recorded during Blizzard's 'OverWatch' and the bio-information collected from various sensors in the mouse.
Keywords
Biometrics; Skin Conductance; Affective Computing;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 Marieke van Dooren, J.J.G. (Gert-Jan) de Vries, Joris H. Janssen, "Emotional sweating across the body: Comparing 16 different skin conductance measurement locations", Physiology & Behavior, Vol. 106, No. 2, pp. 298-304, 2012   DOI
2 Agata Kolakowska, "Recognizing emotions on the basis of keystroke dynamics", Human System Interactions (HSI), 2015 8th International Conference on, 2015
3 Simone Tognetti, Maurizio Garbarino, Andrea Bonarini, "Modeling enjoyment preference from physiological responses in a car racing game" Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games, pp. 321-328, 2010
4 Georgios N. Yannakakis, Héctor P. Martinez, Arnav Jhala, "Towards affective camera control in games", UserModeling and User-Adapted Interaction, Vol. 20, No. 4, pp. 313-340, 2010   DOI
5 Regan L. Mandryk, Kori M. Inkpen, "Physiological indicators for the evaluation of co-located collaborativeplay", Proceeding CSCW'04 Proceedings of the 2004 ACM conference on Computer supported cooperative work, pp. 102-111, 2004
6 Ludger van Dijk , Corry K. van der Sluis, Hylke W. van Dijk, Raoul M. Bongers, "Learning an EMG Controlled Game: Task-Specific Adaptations and Transfer", PLOS ONE, 2016
7 Anton Nijholt, "BCI forGames: A State of the Art Survey", Proceedings of Entertainment Computing - ICEC 2008, pp. 225-228, 2008
8 Y. B. Kim, S. J. Kang, S. H.Lee, J. Y. Jung, H. R. Kam, J. Lee, Y. S. Kim, J. S. Lee and C. H. Kim, "Efficiently Detecting Outlying Behavior in Video-Game Players", PeerJ, 2015
9 C. G. Kohler, T. H. Turner, W.B. Bilker, C. M. Brensinger, S. J. Siegel, S. J. Kanes, R. E. Gur, R. C. Gur, "Facial Emotion Recognition in Schizophrenia: Intensity Effects and Error Pattern", American Journal of Psychiatry, Vol. 160, No. 10, pp. 1768-1744, 2003   DOI
10 C. H. Lee, D. G. Kim, H. Y. Kim, and S. J. Kang, "Developing Affective Computing Game with Player's Bio-Signal", Journal of Korea Game Society, Vol. 16, No. 6, pp. 91-100, 2016   DOI
11 Jing-Kai Lou, Kuan-Ta Chen, Hwai-Jung Hsu, Chin-Laung Lei, "Forecasting online game addictiveness", 2012 11th Annual Workshop on Network and Systems Support for Games (NetGames), 2012
12 Nerosky, http://neurosky.com
13 H. D. Kim, H. C. Yang, and K. B. Sim, "Emotion Recognition Method for Driver Services", Korea Institute of Intelligent System, pp. 438-442, 2017