Games User Research and Physiological Game Evaluation

  • Lennart E. NackeEmail author
Part of the Human–Computer Interaction Series book series (HCIS)


This chapter introduces physiological measures for game evaluation in the context of games user research (GUR). GUR consists of more than playtesting game; it comprises a collection of methods that allow designers to bring their creations closer to the initial vision of the player experience. With the prices of physiological sensors falling, and the advancement of research in this area, physiological evaluation will soon become a standard tool in GUR and game evaluation. Since mixed-method approaches are of increasingly prominent value, this chapter describes core GUR methods with a special focus on physiological evaluation, keeping in mind both benefits and limitations of the approach in academic and industrial applications.


Galvanic Skin Response Heuristic Evaluation Physiological Evaluation Player Experience Game Industry 
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.



This research was supported by the Network of Centres of Excellence (NCE), Graphics, Animation and New Media (GRAND) and NSERC. Dr. Nacke thanks Samantha Stahlke and Rina Wehbe for proofreading the final manuscript.


  1. Ambinder M (2011) Biofeedback in gameplay: how valve measures physiology to enhance gaming experience. Paper presented at the game developers conferenceGoogle Scholar
  2. Bartle R (1996) Hearts, clubs, diamonds, spades: players who suit MUDs. J MUD Res 1(1) 19 pages.
  3. Boucsein W (1992) Electrodermal activity. Plenum Press, New YorkCrossRefGoogle Scholar
  4. Bradley MM, Codispoti M, Cuthbert BN, Lang PJ (2001) Emotion and motivation I: defensive and appetitive reactions in picture processing. Emotion 1(3):276–298CrossRefGoogle Scholar
  5. Brathwaite B, Schreiber I (2008) Challenges for game designers. Charles River Media, BostonGoogle Scholar
  6. Brockmyer JH, Fox CM, Curtiss KA, McBroom E, Burkhart KM, Pidruzny JN (2009) The development of the game engagement questionnaire: a measure of engagement in video game-playing. J Exp Soc Psychol 45(4):624–634. doi:10.1016/j.jesp.2009.02.016CrossRefGoogle Scholar
  7. Buss AH, Perry MP (1992) The aggression questionnaire. J Pers Soc Psychol 63(3):452–459CrossRefGoogle Scholar
  8. Cacioppo JT, Tassinary LG, Fridlund AJ (1990) The skeletomotor system. In: Cacioppo JT, Tassinary LG (eds) Principles of psychophysiology: physical, social, and inferential elements (pp 325–384).Google Scholar
  9. Cambridge University Press, New York, xiii, 914 pp.Google Scholar
  10. Cacioppo JT, Tassinary LG, Berntson GG (2007) Psychophysiological science. In: Cacioppo JT, Tassinary LG, Berntson GG (eds) Handbook of psychophysiology. pp 3–26. Cambridge University Press. 3rd Edition. ISBN: 0521844711Google Scholar
  11. Carnagey NL, Anderson CA, Bushman BJ (2007) The effect of video game violence on physiological desensitization to real-life violence. J Exp Soc Psychol 43(3):489–496CrossRefGoogle Scholar
  12. Carver CS, White TL (1994) Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: the BIS/BAS scales. J Pers Soc Psychol 67(2):319–333CrossRefGoogle Scholar
  13. Chatrian GE, Lettich E, Nelson PL (1988) Modified nomenclature for the “10 %” electrode system. J Clin Neurophysiol: Off Publ Am Electroencephalogr Soc 5(2):183–186CrossRefGoogle Scholar
  14. Damasio AR (1994) Descartes’ error. G.P. Putnam, New YorkGoogle Scholar
  15. Desurvire H, Wiberg C (2008) Master of the game: assessing approachability in future game design. In: CHI ’08 extended abstracts on human factors in computing systems, Florence, Italy, April 5–10, 2008. ACM, New York, pp 3177–3182. doi:10.1145/1358628.1358827.Google Scholar
  16. Desurvire H, Caplan M, Toth JA (2004) Using heuristics to evaluate the playability of games. In: CHI ’04 extended abstracts on Human factors in computing systems, Vienna, Austria, 2004. ACM, pp 1509–1512. doi:10.1145/985921.986102Google Scholar
  17. Duchowski AT (2007) Eye tracking methodology: theory and practice, 2nd edn. Springer, New YorkGoogle Scholar
  18. Eysenck SBG, Eysenck HJ, Barrett P (1985) A revised version of the psychoticism scale. Pers Individ Differ 6(1):21–29CrossRefGoogle Scholar
  19. Fairclough SH (2011) Biometrics and evaluation of gaming experience part two: a thought experiment. Last accessed 20 Oct 2012
  20. Fridlund AJ, Cacioppo JT (1986) Guidelines for human electromyographic research. Psychophysiology 23(5):567–589. doi:10.1111/j.1469-8986.1986.tb00676.xCrossRefGoogle Scholar
  21. Hazlett RL (2006) Measuring emotional valence during interactive experiences: boys at video game play. Paper presented at the Proceedings of the SIGCHI conference on Human Factors in computing systems, Montréal, Québec, Canada. doi:10.1145/1124772.1124925Google Scholar
  22. Jasper HH (1958) Report of the committee on methods of clinical examination in electroencephalography. Electroencephalography and Clinical Neurophysiology 10Google Scholar
  23. Jegers K (2008) Investigating the Applicability of Usability and Playability Heuristics for Evaluation of Pervasive Games. In: Internet and Web Applications and Services, 2008. ICIW ’08. Third International Conference on, 2008. pp 656–661. doi:10.1109/ICIW.2008.54.Google Scholar
  24. Jennett C, Cox AL, Cairns P, Dhoparee S, Epps A, Tijs T, Walton A (2008) Measuring and defining the experience of immersion in games. Int J Hum Comput Stud 66:641–661. doi:10.1016/j.ijhcs.2008.04.004CrossRefGoogle Scholar
  25. John OP, Srivastava S (1999) The big five trait taxonomy: history, measurement, and theoretical perspectives. In: Pervin LA, John OP (eds) Handbook of personality: theory and research. 2nd edn. Guilford Press, New York, pp 102–138Google Scholar
  26. Kivikangas JM, Ekman I, Chanel G, Järvelä S, Salminen M, Cowley B, Henttonen P, Ravaja N (2010) Review on psychophysiological methods in game research. Paper presented at the Proceedings of 1st Nordic DiGRAGoogle Scholar
  27. Koeffel C, Hochleitner W, Leitner J, Haller M, Geven A, Tscheligi M (2010) Using heuristics to evaluate the overall user experience of video games and advanced interaction games evaluating user experience in games. In: Bernhaupt R (ed). Human–computer interaction series. Springer, London, pp 233–256. doi:10.1007/978-1-84882-963-313Google Scholar
  28. Korhonen H, Koivisto EMI (2006) Playability heuristics for mobile games. In: Proceedings of the 8th conference on Human-computer interaction with mobile devices and services, Espoo, Finland, 2006. ACM, pp 9–16. doi:10.1145/1306813.1306828.Google Scholar
  29. Korhonen H, Koivisto EMI (2007) Playability Heuristics for Mobile Multi-player Games. In: International conference on Digital interactive media in entertainment and arts (DIMEA), Perth, Australia, 2007. ACM, pp 28–35 doi:10.1145/1306813.1306828Google Scholar
  30. Lang PJ (1995) The emotion probe. Studies of motivation and attention. Am Psychol 50:372–385CrossRefGoogle Scholar
  31. Larsen RJ, Diener E (1992) Promises and problems with the circumplex model of emotion. Rev pers soc psychol 13:25–59Google Scholar
  32. Larsen JT, McGraw AP, Cacioppo JT (2001) Can people feel happy and sad at the same time? J Pers Soc Psychol 81(4):684–696. doi:10.1037/0022-3514.81.4.684CrossRefGoogle Scholar
  33. LeDoux J (1998) The emotional brain. Orion Publishing Group, LondonGoogle Scholar
  34. Lewis C (1982) Using the thinking-aloud method in cognitive interface design. Vol technical report. IBM TJ Watson Research Center, Yorktown HeightsGoogle Scholar
  35. Likert R (1932) A technique for the measurement of attitudes. Arch Psychol 22(140):1–55Google Scholar
  36. Livingston IJ, Mandryk RL, Stanley KG (2010) Critic-proofing: how using critic reviews and game genres can refine heuristic evaluations. Paper presented at the Proceedings of the International Academic Conference on the Future of Game Design and Technology, Vancouver, British Columbia, Canada doi:10.1145/1920778.1920786Google Scholar
  37. Lykken DT, Venables PH (1971) Direct measurement of skin conductance: a proposal for standardization. Psychophysiology 8(5):656–672. doi:10.1111/j.1469-8986.1971.tb00501.xCrossRefGoogle Scholar
  38. Mandryk R (2008) Physiological measures for game evaluation. In: Isbister K, Schaffer N (eds) Game usability: advice from the experts for advancing the player experience. Morgan Kaufmann, Burlington, pp 207–235Google Scholar
  39. Mandryk RL, Inkpen KM, Calvert TW (2006) using psychophysiological techniques to measure user experience with entertainment technologies. Behav Inform Technol 25(2):141–158. doi:10.1080/01449290500331156CrossRefGoogle Scholar
  40. Mirza-Babaei P, Nacke LE, Gregory J, Collins N, Fitzpatrick G (2013) How does it play better?: exploring user testing and biometric storyboards in games user research. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ‘13). ACM, New York, NY, USA, 1499–1508. doi:10.1145/2470654.2466200.
  41. Nacke L (2009) Affective ludology: scientific measurement of user experience in interactive entertainment. Ph. D. thesis, Blekinge Institute of Technology, KarlskronaGoogle Scholar
  42. Nacke L (2010) Wiimote vs. Controller: Electroencephalographic Measurement of Affective Gameplay Interaction. Paper presented at the Proceedings of Future Play 2010, Vancouver, BCGoogle Scholar
  43. Nacke L, Lindley CA (2008) Flow and Immersion in First-Person Shooters: Measuring the player’s gameplay experience. Paper presented at the Proceedings of the 2008 Conference on Future Play: Research, Play, Share, Toronto, Canada, November 3–5 doi:10.1145/1496984.1496998Google Scholar
  44. Nacke LE, Bateman C, Mandryk RL (2014) BrainHex: A Neurobiological Gamer Typology Survey. Entertain Comput 5:55–62. doi:10.1016/j.entcom.2013.06.002Google Scholar
  45. Nacke LE, Kalyn M, Lough C, Mandryk RL (2011) Biofeedback game design: using direct and indirect physiological control to enhance game interaction. Paper presented at the CHI 2011, Vancouver, BC, Canada. doi:10.1145/1978942.1978958Google Scholar
  46. Nacke LE (2013) An introduction to physiological player metrics for evaluating games. In: Seif El-Nasr M, Drachen A, Canossa A (eds) Game Analytics - Maximizing the Value of Player Data. Springer London, 585–619. doi:10.1007/978-1-4471-4769-5_26Google Scholar
  47. Nielsen J, Molich R (1990) Heuristic evaluation of user interfaces. Paper presented at the Proceedings of the SIGCHI conference on Human factors in computing systems: Empowering people, Seattle, Washington, United States doi:10.1145/97243.97281Google Scholar
  48. Nishimoto S, Vu AT, Naselaris T, Benjamini Y, Yu B, Gallant Jack L (2011) Reconstructing visual experiences from brain activity evoked by natural movies. Curr Biol CB 21(19): 1641–1646 doi:10.1016/j.cub.2011.08.031CrossRefGoogle Scholar
  49. Pessoa L (2008) On the relationship between emotion and cognition. Nat Rev Neurosci 9(2):148–158 doi:10.1038/nrn2317CrossRefGoogle Scholar
  50. Pinelle D, Wong N, Stach T (2008a) Heuristic evaluation for games: usability principles for video game design. In: The 26th annual CHI conference on human factors in computing systems, Florence, Italy. ACM, pp 1453–1462 doi:10.1145/1357054.1357282Google Scholar
  51. Pinelle D, Wong N, Stach T (2008b) Using genres to customize usability evaluations of video games. In: 2008 Conference on future play: research, play, share, Toronto, Ontario, Canada. ACM, pp 129–136 doi:10.1145/1496984.1497006Google Scholar
  52. Pizzagalli DA (2007) Electroencephalography and high-density electrophysiological source localization. In: Cacioppo JT, Tassinary LG, Berntson GG (eds) Handbook of psychophysiology, 3rd edn. Cambridge University Press, New York, pp 56–84Google Scholar
  53. Poels K, et al. (2010) Digital games, the Aftermath: qualitative insights into postgame experiences. Evaluating user experience in games. Springer London, 149–163. doi:10.1007/978-1-84882-963-3_9Google Scholar
  54. Ravaja N, Turpeinen M, Saari T, Puttonen S, Keltikangas-Järvinen L (2008) The psychophysiology of James Bond: phasic emotional responses to violent video game events. Emotion 8(1):114–120. doi:10.1037/1528-3542.8.1.114CrossRefGoogle Scholar
  55. Russell JA (1980) A circumplex model of affect. J Pers Soc Psychol 39(6):1161–1178. doi:10.1037/h0077714CrossRefGoogle Scholar
  56. El-Nasr M, Drachen A, Canossa A (2013) Game analytics: Maximizing the value of player data. Springer London. doi:10.1007/978-1-4471-4769-5Google Scholar
  57. Stemmler G, Aue T, Wacker J (2007) Anger and fear: separable effects of emotion and motivational direction on somatovisceral responses. Int J Psychophysiol 66(2):141–153. doi:10.1016/j.ijpsycho.2007.03.019CrossRefGoogle Scholar
  58. Stern RM, Ray WJ, Quigley KS (2001) Psychophysiological recording, 2nd edn. Oxford University Press, New YorkGoogle Scholar
  59. van Abeelen JHF (1964) Mouse mutants studied by means of ethological methods. Genetica 34(1):79–94. doi:10.1007/bf01664181CrossRefGoogle Scholar
  60. Wehbe RR, Nacke LE (2013) An introduction to EEG analysis techniques and brain-computer interfaces for games user researchers. Proceedings of DiGRA 2013. DiGRA, Atlanta, GA, United States, pp 1–16Google Scholar
  61. White GR, Mirza-Babaei P, McAllister G, Good J (2011) Weak inter-rater reliability in heuristic evaluation of video games. Paper presented at the Proceedings of CHI EA 2011, Vancouver, BC, Canada doi:10.1145/1979742.1979788Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Faculty of Business and Information TechnologyUniversity of Ontario Institute of TechnologyOntarioCanada

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