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Title: Preliminary studies for capturing entertainment through physiology in physical play
Authors: Yannakakis, Georgios N.
Hallam, John
Lund, Henrik Hautop
Keywords: Human-computer interaction
Computer games
Artificial neural networks
Virtual reality
Issue Date: 2007
Publisher: University of Southern Denmark. The Maersk Mc-Kinney Moller Institute
Citation: Yannakakis, G. N., & Hallam, J. (2007). Preliminary studies for capturing entertainment through physiology in physical play. Technical Report TR-2007-5, University of Southern Denmark.
Abstract: This report presents preliminary physical control experiments for capturing and modeling the affective state of entertainment — that is, whether people are having "fun" — of users of the innovative Play-ware playground, an interactive physical playground. The goal is to con-struct, using representative statistics computed from children's physio-logical hear rate (HR) signals, an estimator of the degree to which games provided by the playground engage the players. For this purpose chil-dren's HR signals, and their expressed preferences of how much "fun" particular game variants are, are obtained from experiments using games implemented on the Playware playground. Neuro-evolution techniques combined with feature set selection methods permit the construction of user models that predict reported entertainment preferences given HR features. These models are expressed as artificial neural networks and are demonstrated and evaluated on two Playware games and the pre-liminary control task requiring physical activity. Results demonstrate that the proposed preliminary control experiment is not an appropriate control for physical activity effects since it may generate HR dynamics rather easy to separate from game-play HR dynamics, and allows one to distinguish entertaining game-play from exercise purely on the artificial basis of the kind of physical activity taking place. Conclusions derived from this study constitute the basis for the design of more appropriate control experiments and user models in future studies.
ISSN: 16014219
Appears in Collections:Scholarly Works - InsDG

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