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.

Acknowledgments

We gratefully acknowledge the help of Professor Eric Vanman of the Psychology department of Georgia State University during this work.