Characterizing player's experience from physiological signals using fuzzy decision trees Conference Paper


Authors: Levillain, Florent; Orero, Joseph Onderi; Rifqi, Maria; Bouchon-Meunier, Bernadette
Title: Characterizing player's experience from physiological signals using fuzzy decision trees
Abstract: In the recent years video games have enjoyed a dramatic increase in popularity, the growing market being echoed by a genuine interest in the academic field. With this flourishing technological and theoretical efforts, there is need to develop new evaluative methodologies for acknowledging the various aspects of the player's subjective experience, and especially the emotional aspect. In this study, we addressed the possibility of developing a model for assessing the player's enjoyment (amusement) with respect to challenge in an action game. Our aim was to explore the viability of a generic model for assessing emotional experience during gameplay from physiological signals. In particular, we propose an approach to characterize the player's subjective experience in different psychological levels of enjoyment from physiological signals using fuzzy decision trees.
Keywords: Biomedical monitoring; Computational intelligence; Decision trees; Feature extraction; Games; Heart rate; Machine learning
Conference Title: Unknown (978-1-4244-6295-7 )
Conference Dates: 18-21 Aug. 2010
Conference Location: Dublin
ISBN: 978-1-4244-6295-7
Publisher: IEEE  
Location: 10.1109/ITW.2010.5593370
Date Published: 2015-04-09
Start Page: 75
End Page: 82
DOI/URL:
Notes: Published in: Computational Intelligence and Games (CIG), 2010 IEEE Symposium
SU Authors
  1. Dr. Joseph Orero
    6 Orero
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