Psychophysiological Indicators for Modeling User Experience in Interactive Digital Entertainment.

Analyses of user experience in the electronic entertainment industry currently rely on self-reporting methods, such as surveys, ratings, focus group interviews, etc. We argue that self-reporting alone carries inherent problems-mainly the misinterpretation and temporal delay during longer experiments-and therefore, should not be used as a sole metric. To tackle this problem, we propose the possibility of modeling consumer experience using psychophysiological measures and demonstrate how such models can be trained using machine learning methods.