Emotionbike: A study of provoking emotions in cycling exergames

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Abstract

In this work, we investigate the effect of how exercise game design elements generate deliberate real-time sensed emotional responses in gamers. Our experimental setup consists of a cycling game controller, a designed 3D first-person cycling game to provoke emotions, a data recording system, and an emotion analysis system. The physical cycling game controller is an enhanced computer controlled bike-exercise-trainer that enables handle bar steering and sets pedal resistance. Our developed 3D first person cycling game provokes emotions with game elements in different game settings: timed race, parcours traversal, and virtual world exploration. Our recording system synchronously captures video, game controller activity, and game events for emotion analysis. In this case study, we show evidence that crafted computer exergame elements are able to provoke subject emotions displayed in their facial expressions, which can be quantified with our developed analysis method. The game elements selected in the specific gameplay situations follow patterns that give inside and judge of individual players involvement and emotional tension. Our emotion analysis of game events provides insights into player reactions during specific game situations. Our results show that strong differing responses by individuals may be taken into account in the design of game mechanics. For example, the falling event of level 3 showed that two opposing strong reactions could be triggered in players. The emotion analysis methods may be used in other types of games. Hereby we believe that a combination of questionnaires and our in situ emotion analysis provide valuable feedback to aid decision in for game design and game mechanics.

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Müller, L., Zagaria, S., Bernin, A., Amira, A., Ramzan, N., Grecos, C., & Vogt, F. (2015). Emotionbike: A study of provoking emotions in cycling exergames. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9353, pp. 155–168). Springer Verlag. https://doi.org/10.1007/978-3-319-24589-8_12

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