|
 ABSTRACT
This paper proposes an approach based on emotion recognition to maintain engagement of players in a game by modulating the game difficulty. Physiological and questionnaire data were gathered from 20 players during and after playing a Tetris game at different difficulty levels. Both physiological and self-report analyses lead to the conclusion that playing at different levels gave rise to different emotional states and that playing at the same level of difficulty several times elicits boredom. Emotion assessment from physiological signals was performed using a SVM (Support Vector Machine). An accuracy of 53.33% was obtained on the discrimination of three emotional classes, namely boredom, anxiety, engagement.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
| |
1
|
|
| |
2
|
Chanel, G., Ansari-Asl, K. and Pun, T., 2007. Valence-arousal evaluation using physiological signals in an emotion recall paradigm. in IEEE SMC and International Conference on Systems, Man and Cybernetics, Smart cooperative systems and cybernetics: advancing knowledge and security for humanity, (Montreal, Canada, 2007).
|
| |
3
|
Chanel, G., Kronegg, J., Grandjean, D. and Pun, T. Emotion assessment: Arousal evaluation using EEG's and peripheral physiological signals in Multimedia Content Representation, Classification and Security B. Gunsel, A. K. J., A. M. Tekalp, B. Sankur ed., Springer LNCS, Istanbul, Turkey, 2006, 530--537.
|
 |
4
|
|
| |
5
|
Cowie, R., Douglas-Cowie, E., Tsapatsoulis, N., Votsis, G., Kollias, S., Fellenz, W. and Taylor, J. G. 2001. Emotion recognition in human-computer interaction. IEEE Signal Processing Magazine, 18 (1). 32--80.
|
| |
6
|
Csikszentmihalyi, M. Flow: the psychology of optimal experience. New York: Harper Collins, 1991.
|
| |
7
|
Fairclough, S. H., 2007. Psychophysiological inference and physiological computer games. in Brainplay'07: Brain-Computer Interfaces and Games, Workshop at the Int. Conf. on Advances in Computer Entertainment, (Salzburg, Austria 2007).
|
| |
8
|
Healey, J. A. Wearable and Automotive Systems for Affect Recognition from Physiology Electrical Engineering and Computer Science Dept., MIT, 2000.
|
| |
9
|
Kim, J., 2004. Emotion Recognition from Physiological Measurement. in Humaine European Network of Excellence Workshop, (Santorini, Greece, 2004).
|
| |
10
|
Lang, P. J., Greenwald, M. K., Bradley, M. M. and Hamm, A. O. 1993. Looking at pictures: affective, facial, visceral, and behavioral reactions. Psychophysiology, 30 (3). 261--273.
|
| |
11
|
|
| |
12
|
Morris, J. D. 1995. SAM:The Self-Assessment Manikin, An Efficient Cross-Cultural Measurement of Emotional Response. Journal of Advertising Research, 35 (6).
|
| |
13
|
|
| |
14
|
Prensky, M. Computer games and learning: digital game-based learning in Handbook of computer games studies Raessens, J. and Goldstein, J. eds., The MIT Press, Cambridge, MA, 2005.
|
| |
15
|
Rainville, P., Bechara, A., Naqvi, N. and Damasio, A. R. 2006. Basic emotions are associated with distinct patterns of cardiorespiratory activity. International Journal of Psychophysiology, 61 (1). 5--18.
|
| |
16
|
Rani, P., Sarkar, N. and Liu, C., 2005. Maintaining Optimal Challenge in Computer Games through Real-Time Physiological Feedback. in 11th HCI International, (Las Vegas, USA, 2005), Lawrence Erlbaum Associates, Inc.
|
| |
17
|
Sinha, R., Lovallo, W. R. and Parsons, O. A. 1992. Cardiovascular differentiation of emotions. Psychosomatic Medicine, 54 (4). 422--435.
|
CITED BY 5
|
|
|
|
|
Theofanis Kannetis , Alexandros Potamianos , Georgios N. Yannakakis, Fantasy, curiosity and challenge as adaptation indicators in multimodal dialogue systems for preschoolers, Proceedings of the 2nd Workshop on Child, Computer and Interaction, p.1-6, November 05-05, 2009, Cambridge, Massachusetts
|
|
|
|
|
|
|
|
|
|
|
Adobe Acrobat
QuickTime
Windows Media Player
Real Player
Pdf
J.4