The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Dynamic Difficulty Adjustment in Computer Games Through Real-Time Anxiety-Based Affective Feedback
Abstract
A number of studies in recent years have investigated the dynamic difficulty adjustment (DDA) mechanism in computer games to automatically tailor gaming experience to individual player's characteristics. Although most of these existing works focus on game adaptation based on player's performance, affective state experienced by the players could play a key role in gaming experience and may provide a useful indicator for a DDA mechanism. In this article, an affect-based DDA was designed and implemented for computer games. In this DDA mechanism, a player's physiological signals were analyzed to infer his or her probable anxiety level, which was chosen as the target affective state, and the game difficulty level was automatically adjusted in real time as a function of the player's affective state. Peripheral physiological signals were measured through wearable biofeedback sensors and several physiological indices were explored to determine their correlations with anxiety. An experimental study was conducted to evaluate the effects of the affect-based DDA on game play by comparing it with a performance-based DDA. This is the first time, that is known, that the impact of a real-time affect-based DDA has been demonstrated experimentally.
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Cited by
Hamari, J., Shernoff, D. J., Rowe, E., Coller, B., Asbell-Clarke, J., & Edwards, T. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2015.07.045 · Cited by 1,713
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Emotion Assessment From Physiological Signals for Adaptation of Game Difficulty
Chanel, G., Rebetez, C., Bétrancourt, M., & Pun, T. (2011) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/tsmca.2011.2116000 · Cited by 398
A review of the use of psychophysiological methods in game research
Kivikangas, J. M., Chanel, G., Cowley, B., Ekman, I., Salminen, M., Järvelä, S., & Ravaja, N. (2011) · Journal of Gaming & Virtual Worlds · doi:10.1386/jgvw.3.3.181_1 · Cited by 288
A neurofeedback video game (MindLight) to prevent anxiety in children: A randomized controlled trial
Schoneveld, E. A., Malmberg, M., Lichtwarck-Aschoff, A., Verheijen, G. P., Engels, R. C. M. E., & Granic, I. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.05.005 · Cited by 174
Metadata
- Authors
- Liu, C., Agrawal, P., Sarkar, N., & Chen, S.
- Venue
- International Journal of Human-Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2009-08-12
- Volume
- 25
- Issue
- 6
- Pages
- 506-529
- ISSN
- 1044-7318 (ISSN-L)
- 1532-7590
- OpenAlex
- W2005451131
- Cited by
- 259
- References
- 48
- FWCI
- 9.64
- Type
- journal article
- Language
- en
- Open access
- closed
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- Liu, C., Agrawal, P., Sarkar, N., & Chen, S. (2009). Dynamic Difficulty Adjustment in Computer Games Through Real-Time Anxiety-Based Affective Feedback. International Journal of Human-Computer Interaction. https://doi.org/10.1080/10447310902963944
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
