research-article

Classifying input for active games

Authors:

Tadeusz Stach,

T. C. Nicholas Graham,

Matthew Brehmer,

Andreas HollatzAuthors Info & Claims

ACE '09: Proceedings of the International Conference on Advances in Computer Entertainment Technology

Pages 379 - 382

https://doi.org/10.1145/1690388.1690465

Published: 29 October 2009 Publication History

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Abstract

Active games are video games that involve physical activity. Active games capture input via a variety of devices such as accelerometers, cameras, pressure sensors and exercise equipment. Although active games have become highly popular, the interaction styles they support are poorly understood, and largely driven by the capabilities of individual hardware devices. In order to allow for a standard development approach, a better understanding of the interaction found in active games is required. We have investigated existing commercial and academic games in order to classify input for active games. Our classification abstracts input from hardware, providing a better understanding of the interaction itself. Our ultimate goal is to make it easier to develop active games independently of underlying input hardware.

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Cited By

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Cao LPeng CDong Y(2021)Ellic’s Exercise Class: promoting physical activities during exergaming with immersive virtual realityVirtual Reality10.1007/s10055-020-00477-z25:3(597-612)Online publication date: 1-Sep-2021
https://dl.acm.org/doi/10.1007/s10055-020-00477-z
Petsani DKostantinidis EZilidou VBamidis P(2018)Exploring health profiles from physical and cognitive serious game analytics2018 2nd International Conference on Technology and Innovation in Sports, Health and Wellbeing (TISHW)10.1109/TISHW.2018.8559562(1-6)Online publication date: Jun-2018
https://doi.org/10.1109/TISHW.2018.8559562
van Delden RGerritsen SHeylen DReidsma D(2018)Co-located augmented play-spaces: past, present, and perspectivesJournal on Multimodal User Interfaces10.1007/s12193-018-0269-z12:3(225-255)Online publication date: 14-Aug-2018
https://doi.org/10.1007/s12193-018-0269-z
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Index Terms

Classifying input for active games
1. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

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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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 October 2009

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ACE '09

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ACE '09: International Conference in Advances in Computer Entertainment Technology

October 29 - 31, 2009

Athens, Greece

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Overall Acceptance Rate 36 of 90 submissions, 40%

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Cited By

View all

Cao LPeng CDong Y(2021)Ellic’s Exercise Class: promoting physical activities during exergaming with immersive virtual realityVirtual Reality10.1007/s10055-020-00477-z25:3(597-612)Online publication date: 1-Sep-2021
https://dl.acm.org/doi/10.1007/s10055-020-00477-z
Petsani DKostantinidis EZilidou VBamidis P(2018)Exploring health profiles from physical and cognitive serious game analytics2018 2nd International Conference on Technology and Innovation in Sports, Health and Wellbeing (TISHW)10.1109/TISHW.2018.8559562(1-6)Online publication date: Jun-2018
https://doi.org/10.1109/TISHW.2018.8559562
van Delden RGerritsen SHeylen DReidsma D(2018)Co-located augmented play-spaces: past, present, and perspectivesJournal on Multimodal User Interfaces10.1007/s12193-018-0269-z12:3(225-255)Online publication date: 14-Aug-2018
https://doi.org/10.1007/s12193-018-0269-z
Park TLee UMacKenzie SMoon MHwang ISong JJones MPalanque PSchmidt AGrossman T(2014)Human factors of speed-based exergame controllersProceedings of the SIGCHI Conference on Human Factors in Computing Systems10.1145/2556288.2557091(1865-1874)Online publication date: 26-Apr-2014
https://dl.acm.org/doi/10.1145/2556288.2557091
Schneider OMacLean KAltun KKaruei IWu MKim JNichols JSzekely P(2013)Real-time gait classification for persuasive smartphone appsProceedings of the 2013 international conference on Intelligent user interfaces10.1145/2449396.2449418(161-172)Online publication date: 19-Mar-2013
https://dl.acm.org/doi/10.1145/2449396.2449418
Al-Hrathi RKarime AAl-Osman HSaddik A(2012)Exerlearn BikeProceedings of the 2012 IEEE International Conference on Multimedia and Expo Workshops10.1109/ICMEW.2012.91(489-494)Online publication date: 9-Jul-2012
https://dl.acm.org/doi/10.1109/ICMEW.2012.91
Staiano ACalvert S(2011)The promise of exergames as tools to measure physical healthEntertainment Computing10.1016/j.entcom.2011.03.0082:1(17-21)Online publication date: Jan-2011
https://doi.org/10.1016/j.entcom.2011.03.008
Brehmer MGraham TStach TKapralos BHogue AXu S(2010)Activate your GAIMProceedings of the International Academic Conference on the Future of Game Design and Technology10.1145/1920778.1920800(151-158)Online publication date: 6-May-2010
https://dl.acm.org/doi/10.1145/1920778.1920800
Alankus GLazar AMay MKelleher CMynatt EFitzpatrick GHudson SEdwards KRodden T(2010)Towards customizable games for stroke rehabilitationProceedings of the SIGCHI Conference on Human Factors in Computing Systems10.1145/1753326.1753649(2113-2122)Online publication date: 10-Apr-2010
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