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Creating an Emotionally Adaptive Game

  • Tim Tijs
  • Dirk Brokken
  • Wijnand IJsselsteijn
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5309)

Abstract

To optimize a player’s experience, an emotionally adaptive game continuously adapts its mechanics to the player’s emotional state, measured in terms of emotion-data. This paper presents the first of two studies that aim to realize an emotionally adaptive game. It investigates the relations between game mechanics, a player’s emotional state and his/her emotion-data. In an experiment, one game mechanic (speed) was manipulated. Emotional state was self-reported in terms of valence, arousal and boredom-frustration-enjoyment. In addition, a number of (mainly physiology-based) emotion-data features were measured. Correlations were found between the valence/arousal reports and the emotion-data features. In addition, seven emotion-data features were found to distinguish between a boring, frustrating and enjoying game mode. Taken together, these features convey sufficient data to create a first version of an emotionally adaptive game.

Keywords

Adaptivity personalization computer games affective loop psychophysiology emotions 

References

  1. 1.
    Adams, E., Rollings, A.: Game Design and Development; Fundamentals of Game Design. Pearson Education, NJ (2007)Google Scholar
  2. 2.
    Malone, T.W.: What Makes Computer Games Fun? Byte 6, 258–277 (1981)Google Scholar
  3. 3.
    Koster, R.: Theory of Fun for Game Design. Paraglyph Press, Phoenix (2004)Google Scholar
  4. 4.
    Saari, T., Ravaja, N., Laarni, J., Kallinen, K., Turpeinen, M.: Towards Emotionally Adapted Games. In: Proceedings of Presence 2004, Valencia, Spain, pp. 182–189 (2004)Google Scholar
  5. 5.
    Pagulayan, R.J., Keeker, K., Wixon, D., Romero, R., Fuller, T.: User-centered design in games. In: Jacko, J., Sears, A. (eds.) Handbook for Human–Computer Interaction in Interactive Systems, pp. 883–906. Lawrence Erlbaum Associates Inc., Mahwah (2002)Google Scholar
  6. 6.
    Bartle, R.A.: Hearts, Clubs, Diamonds, Shades: Players who suit MUDs, http://www.mud.co.uk/richard/hcds.htm
  7. 7.
    Sundström, P., Ståhl, A., Höök, K.: eMoto - A User-Centred Approach to Affective Interaction. In: Tao, J., Tan, T., Picard, R.W. (eds.) ACII 2005. LNCS, vol. 3784. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  8. 8.
    Picard, R.W.: Affective Computing. MIT Press, Cambridge (1997)CrossRefGoogle Scholar
  9. 9.
    Ekman, P.: An Argument for Basic Emotions. Cognition and Emotion 6, 169–200 (1992)CrossRefGoogle Scholar
  10. 10.
    Lang, P.J.: The emotion probe: Studies of Motivation and Attention. American Psychologist 50, 372–385 (1995)CrossRefGoogle Scholar
  11. 11.
    Polaine, A.: The flow principle in interactivity. In: Proceedings of 2nd Australasian Conference on Interactive Entertainment, Sydney, Australia, pp. 151–158 (2005)Google Scholar
  12. 12.
    Hunicke, R., LeBlanc, M., Zubek, R.: MDA: A Formal Approach to Game Design and Game Research. In: Proceedings of the Challenges in Game AI Workshop. Nineteenth National Conference on Artificial Intelligence, San Jose, CA (2004)Google Scholar
  13. 13.
    Csikszentmihalyi, M.: Finding flow: The Psychology of Engagement with Everyday Life. Basic Books, NY (1997)Google Scholar
  14. 14.
    Ermi, L., Mäyrä, F.: Proceedings of DiGRA 2005, Vancouver, Canada (2005)Google Scholar
  15. 15.
    Schaefer, F., Haarmann, Boucsein, W.: The Usability of Cardiovascular and Electrodermal Measures for Adaptive Automation. In: Westerink, J.H.D.M., Ouwerkerk, M., Overbeek, T.J.M., Pasveer, W.F., De Ruyter, B. (eds.) Probing Experience: From Assessment of User Emotions and Behavior to Development of Products. Philips Research Book Series, vol. 8, pp. 235–243 (2008)Google Scholar
  16. 16.
    Takahashi, M., Tsuyoshi, A., Kuba, O., Yoshikawa, H.: Experimental Study Toward Mutual Adaptive Interface. In: Proceedings of the 3rd IEEE International Conference on Robot and Human Communication, Nagoya, Japan, pp. 271–276 (1994)Google Scholar
  17. 17.
    Rani, P., Sarkar, N., Liu, C.: Maintaining Optimal Challenge in Computer Games Through Real-Time Physiological Feedback. In: Proceedings of the 1st International Conference on Augmented Cognition, Las Vegas, NV (2005)Google Scholar
  18. 18.
    Journey to Wild Divine, http://www.wilddivine.com
  19. 19.
    Bersak, D., McDarby, G., Augenblick, N., McDarby, P., McDonnell, D., McDonald, B., Karkun, R.: Intelligent Biofeedback Using an Immersive Competitive Environment. In: Abowd, G.D., Brumitt, B., Shafer, S. (eds.) UbiComp 2001. LNCS, vol. 2201. Springer, Heidelberg (2001)Google Scholar
  20. 20.
  21. 21.
    Saari, T.: Mind-Based Media and Communications Technologies. How the Form of Information Influences Felt Meaning. Acta Universitatis Tamperensis 834. Tampere University Press, Tampere (2001)Google Scholar
  22. 22.
    Saari, T., Ravaja, N., Turpeinen, M., Kallinen, K.: Emotional Regulation System for Emotionally Adapted Games. In: Proceedings of FuturePlay 2005, Michigan State University, MI (2005)Google Scholar
  23. 23.
    Öhman, A.: The Psychophysiology of Emotion: An Evolutionary-Cognitive Perspective. In: Ackles, P.K., Jennings, J.R., Coles, M.G.H. (eds.) Advances in Psychophysiology, vol. 2, pp. 79–127. JAI Press, Greenwich (1987)Google Scholar
  24. 24.
    Fasel, B., Luettin, J.: Automatic Facial Analysis: A Survey. IDIAP Research Report (IDIAP RR 99-19). Pattern Recognition 36(1), 259–275 (2003)CrossRefzbMATHGoogle Scholar
  25. 25.
    Van den Hoogen, W., IJsselsteijn, W.A., de Kort, Y.A.W., Poels, K.: Towards Real-Time Behavioral Indicators of Player experiences: Pressure patterns and Postural Responses. In: Proceedings of the 6th International Conference on Methods and Techniques in Behavioral Research, Maastricht, The Netherlands (2008)Google Scholar
  26. 26.
    Ravaja, N.: Contributions of Psychophysiology to Media Research: Review and Recommendations. Media Psychology 6, 193–235 (2004)CrossRefGoogle Scholar
  27. 27.
    Yannakakis, G.N., Hallam, J., Lund, H.H.: Entertainment Capture through Heart Rate Activity in Physical Interactive Playgrounds. User Modeling and User-Adapted Interaction, Special Issue on Affective Modeling and Adaptation 18(1-2), 207–243 (2008)CrossRefGoogle Scholar
  28. 28.
    Vicente, K.J., Thornton, D.C., Moray, N.: Spectral Analysis of Sinus Arrhythmia: A Measure of Mental Effort. Human Factors 29(2), 171–182 (1987)Google Scholar
  29. 29.
    Veltman, J.A., Gaillard, A.W.K.: Indices of Mental Workload in a Complex Task Environment. Neuropsychobiology 28, 72–75 (1993)CrossRefGoogle Scholar
  30. 30.
    Wientjes, C.J.E.: Respiration in Psychology: Methods and Applications. Biological Psychology 34, 179–204Google Scholar
  31. 31.
    Mahlke, S., Minge, M., Thüring, M.: Measuring Multiple Components of Emotions in Interactive Contexts. In: Extended Abstracts of CHI 2006, Montréal, Canada (2006)Google Scholar
  32. 32.
    Partala, T.: Affective Information in Human-Computer Interaction. Academic Dissertation, Department of Computer Sciences, University of Tampere, Finland (2005)Google Scholar
  33. 33.
    Hazlett, R.L., Benedek, J.: Measuring emotional valence to understand the user’s experience of software. Int. J. Hum.-Comput. Stud. 65(4), 306–314 (2007)CrossRefGoogle Scholar
  34. 34.
    Luczak, H., Göbel, M.: Signal Processing and Analysis in Application. In: Backs, R.W., Boucsein, W. (eds.) Engineering Psychophysiology: Issues and Applications, pp. 79–110. Lawrence Erlbaum, Mahwah (2000)Google Scholar
  35. 35.
    Lacey, J.I., Lacey, B.C.: Verification and extension of the principle of autonomic response-stereotypy. Am. J. Psychol. 71, 50–73 (1958)CrossRefGoogle Scholar
  36. 36.
    Mandryke, R.L., Atkins, M.S.: A Fuzzy Physiological Approach for Continuously Modeling Emotion During Interaction with Play Technologies. International Journal of Human-Computer Studies 65, 329–347 (2007)CrossRefGoogle Scholar
  37. 37.
    Thayer, J.F., Friedman, B.H.: The Design and Analysis of Experiments in Engineering Psychophysiology. In: Backs, R.W., Boucsein, W. (eds.) Engineering Psychophysiology: Issues and Applications, pp. 59–78. Lawrence Erlbaum, Mahwah (2000)Google Scholar
  38. 38.
    Overmars, M., McQuown, B.: Pacman.GM6 [computer software]Google Scholar
  39. 39.
    Yannakakis, G.N., Hallam, J.: Towards Optimizing Entertainment in Computer Games. Applied Artificial Intelligence 21, 933–971 (2007)CrossRefGoogle Scholar
  40. 40.
    Waterink, W.: Facial Muscle Activity as an Index of Energy Mobilization During Processing of Information: An EMG Study. Doctoral Thesis, Tilburg University, Tilburg, The Netherlands (1997)Google Scholar
  41. 41.
    Höök, K., Ståhl, A., Sundström, P., Laaksolahti, J.: Interactional Empowerment. In: Proceedings of CHI 2008, Florence, Italy, pp. 647–656. ACM Press, New York (2008)Google Scholar
  42. 42.
    Picard, R., Vyzas, E., Healey, J.: Toward Machine Emotional Intelligence: Analysis of Affective Physiological State. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(10), 1175–1191 (2001)CrossRefGoogle Scholar
  43. 43.
    Van den Broek, E.L., Schut, M.H., Westerink, J.H.D.M., Van Herk, J., Tuinenbreijer, K.: Computing Emotions Awareness through Facial Electromyography. In: Huang, T.S., Sebe, N., Lew, M., Pavlović, V., Kölsch, M., Galata, A., Kisačanin, B. (eds.) ECCV 2006 Workshop on HCI. LNCS, vol. 3979(12), pp. 52–63. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  44. 44.
    Wilder, J.: Stimulus and Response: The Law of the Initial Value. J Wright, Bristol, England (1967)Google Scholar
  45. 45.
    Berntson, G.G., Cacioppo, J.T., Quigley, K.S.: Autonomic Determinism: The Modes of Autonomic Control, the Doctrine of Autonomic Space, and the Laws of Autonomic Constraint. Psychological Review 98(4), 459–487 (1991)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2008

Authors and Affiliations

  • Tim Tijs
    • 1
  • Dirk Brokken
    • 2
  • Wijnand IJsselsteijn
    • 3
  1. 1.User-System Interaction Program, Department of Industrial DesignEindhoven University of TechnologyEindhovenThe Netherlands
  2. 2.Philips Research Laboratories EuropeEindhovenThe Netherlands
  3. 3.Human-Technology Interaction Group, Department of Technology ManagementEindhoven University of TechnologyEindhovenThe Netherlands

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