Emotions Detection Through the Analysis of Physiological Information During Video Games Fruition

Games are interactive tools able to arouse emotions in the user. This is particularly relevant in Serious Games, where the main goal could be educational, pedagogical, etc. Therefore, understanding the players’ emotions during the game fruition could provide a valid support to the developers and researchers in video games field in order to design a more effective product. The presented research is a starting point to propose a framework for the determination of the player emotions through physiological information. We acquire several signals: facial electromyography, electrocardiogram, galvanic skin response, and respiration rate. We then compare the data to an emotional player assessment, defined using a valence and an arousal vector, through the application of Machine Learning techniques. The obtained results seem to suggest that the proposed approach can represent a valid tool to analyze the players’ emotions.