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Towards tailoring player experience in physical Wii games: a case study on relaxation

Published: 29 October 2009 Publication History

Abstract

In this study we construct an artificial neural network model of players' relaxation preferences while playing a physical Wii game. Developed technology will assist game designers to automate a part of the game design and balancing features, and create physical Wii games with adaptive experiences for the player. The model is trained on data derived from the player-Wii interaction which include physiological response, Wii Remote gesture and game data. In this study the developed relaxation model proved to achieve a highest classification accuracy of 78.42%. Furthermore, the restriction of input data to Wii Remote specific features and the possibility of using this model for tailoring the player experience are discussed.

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cover image ACM Other conferences
ACE '09: Proceedings of the International Conference on Advances in Computer Entertainment Technology
October 2009
456 pages
ISBN:9781605588643
DOI:10.1145/1690388
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 29 October 2009

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Author Tags

  1. affective computing
  2. emotion
  3. machine learning
  4. physical interactive games
  5. physiology
  6. tailoring player experience

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