Modeling enjoyment preference from physiological responses in a car racing game

We propose a framework to estimate player enjoyment preference from physiological signals. This can produce objective measures that could be used to adapt dynamically a game to maintain the player in an optimal status of enjoyment. We present a case study on The Open Racing Car Simulator (TORCS) video game. In particular, we focus both on the experimental protocol, which we designed with special attention to produce physiological responses related to the game experience only, and on signal analysis, which produces a simple and general model good enough to estimate player enjoyment preference in real applications.