Affective games:a multimodal classification system

Affective gaming is a relatively new field of research that exploits human emotions to influence gameplay for an enhanced player experience. Changes in player’s psychology reflect on their behaviour and physiology, hence recognition of such variation is a core element in affective games. Complementary sources of affect offer more reliable recognition, especially in contexts where one modality is partial or unavailable. As a multimodal recognition system, affect-aware games are subject to the practical difficulties met by traditional trained classifiers. In addition, inherited game-related challenges in terms of data collection and performance arise while attempting to sustain an acceptable level of immersion. Most existing scenarios employ sensors that offer limited freedom of movement resulting in less realistic experiences. Recent advances now offer technology that allows players to communicate more freely and naturally with the game, and furthermore, control it without the use of input devices. However, the affective game industry is still in its infancy and definitely needs to catch up with the current life-like level of adaptation provided by graphics and animation

Hearth: A Game Supporting Non-Intrusive and Concurrent Tracking of Player Emotion and Mouse Usage

Empirical evidence has supported the idea that eSports players\u27 emotions could be reflected in their mouse usage. Still, findings from IS literature on the exact relationships between users\u27 mouse usage patterns and their emotional states have been mixed. Possible causes include adjustment effects and offsetting effects. To address these problems, this study proposes a self-developed game named Hearth, which supports non-intrusive and concurrent tracking of players\u27 emotions and mouse usage. The game design supports the examination of the two possible effects. Results show that negative emotion was positively associated with the total mouse movement distance in a game turn, average task-level distance, and average task-level speed. Moreover, the open-source game proposed in this study facilitates further data collection from natural experiments due to its triadic design that addresses reality, meaning, and play

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion