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Game Analytics pp 585–619Cite as

An Introduction to Physiological Player Metrics for Evaluating Games

Abstract

Evaluating affective user experience in games is an important component of the growing field of game user research, because compelling gameplay experiences incorporate meaningful and, therefore, emotional player decisions. This makes evaluating player emotions and player visceral physiological reactions a fascinating field of study for game researchers. With their recent success in the human factors domain, physiological metrics, which complement game metrics, have been successfully used to study player engagement and emotion in research and industry. This chapter provides a brief introduction to and primer of physiological measures currently used in game research and discusses the benefits and challenges of this quantitative method of game user research.

Keywords

  • Death Event
  • Skin Conductance Level
  • Body Response
  • Player Experience
  • Psychophysiological Measure

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

  1. 1.

    A stimulus in psychological research is something (could be an event or an object) that evokes a body or mind response.

  2. 2.

    50/60 Hz is the electrical energy frequency that can come from lights, power supplies and other devices in your experiment environment.

  3. 3.

    Another way of analysing EEG is through Event-Related Potentials or Mu Rhythm, which I do not cover in this chapter.

  4. 4.

    http://hcigames.businessandit.uoit.ca

  5. 5.

    For example, participants in an experiment cannot chew gum, laugh, or talk during facial EMG, because this will introduce large artifacts in your EMG data.

  6. 6.

    The usual processing procedure is signal smoothing (often at half of the recording frequency, for example 0.5 s at 2 kHz recordings), baseline subtraction, and sometimes a logarithmic normalization. Depending on the system, an additional bandpass filter (high: 10Hz, low: 400Hz) or a Butterworth lowpass filter of 500Hz are necessary.

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Acknowledgements

Thanks to Pejman Mirza-Babaei for his initial feedback and Anders Drachen for his encouragement and feedback on this chapter. This research was supported by the Network of Centres of Excellence (NCE), Graphics, Animation and New Media (GRAND), NSERC, and SSHRC IMMERSe (895-2011-1014).

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  1. HCI and Game Science Group, Faculty of Business and Information Technology, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, L1H 7K4, ON, Canada

    Lennart E. Nacke

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  1. College of Arts, Media and Design, Northeastern University, Huntington Avenue 360, Boston, 02115, Massachusetts, USA

    Magy Seif El-Nasr

  2. College of Arts, Media and Design, Northeastern University, Huntington Avenue 360, Boston, 02115, Massachusetts, USA

    Anders Drachen

  3. College of Arts, Media and Design, Northeastern University, Huntington Avenue 360, Boston, 02115, Massachusetts, USA

    Alessandro Canossa

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About the Author

Dr. Lennart E. Nacke is an Assistant Professor for Human-Computer Interaction and Game Science in the Faculty of Business and Information Technology at the University of Ontario Institute of Technology (UOIT) in Canada and currently also a visiting lecturer at the Department of Informatics at the University of Sussex. He is working on projects that deal with the cognitive and emotional side of playing games. His goal is to describe, analyse and have computers and machines react to the thoughts and feelings you have when you are fully engaged in playing a video game. With this research we can start understanding the effects of video games (positive and negative). Using body sensor technology, for example, sensors for brainwaves, heart rate, or muscle tension, Dr. Nacke taps into some of video gaming’s most motivating features to improve our physical fitness and mental wellbeing. His research is funded nationally and internationally and his publications have won best paper honourable mention (awarded to the top 5%) and best paper awards (awarded to the top 1%) at the premier human-computer interaction conferences CHI 2011 and CSCW 2012. He also writes a blog at www.acagamic.com and you can find out more about his research group at http://hcigames.businessandit.uoit.ca

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Nacke, L.E. (2013). An Introduction to Physiological Player Metrics for Evaluating Games. In: Seif El-Nasr, M., Drachen, A., Canossa, A. (eds) Game Analytics. Springer, London. https://doi.org/10.1007/978-1-4471-4769-5_26

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