Measuring Immersion and Affect in a Brain-Computer Interface Game

  • Gido Hakvoort
  • Hayrettin Gürkök
  • Danny Plass-Oude Bos
  • Michel Obbink
  • Mannes Poel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6946)

Abstract

Brain-computer interfaces (BCIs) have widely been used in medical applications, to facilitate making selections. However, whether they are suitable for recreational applications is unclear as they have rarely been evaluated for user experience. As the scope of the BCI applications is expanding from medical to recreational use, the expectations of BCIs are also changing. Although the performance of BCIs is still important, finding suitable BCI modalities and investigating their influence on user experience demand more and more attention. In this study a BCI selection method and a comparable non-BCI selection method were integrated into a computer game to evaluate user experience in terms of immersion and affect. An experiment with seventeen participants showed that the BCI selection method was more immersive and positively affective than the non-BCI selection method. Participants also seemed to be more indulgent towards the BCI selection method.

Keywords

Brain-computer interfaces affective computing immersion games 

References

  1. 1.
    Beverina, F., Palmas, G., Silvoni, S., Piccione, F., Giove, S.: User adaptive BCIs: SSVEP and P300 based interfaces. PsychNology Journal 1(4), 331–354 (2003)Google Scholar
  2. 2.
    Bin, G., Gao, X., Yan, Z., Hong, B., Gao, S.: ShangkaiGao: An online multi-channel SSVEP-based brain–computer interface using a canonical correlation analysis method. Journal of Neural Engineering 6(4), 46002 (2009)CrossRefGoogle Scholar
  3. 3.
    Bradley, M.M., Lang, P.J.: Measuring emotion: The self-assessment manikin and the semantic differential. Journal of Behavior Therapy and Experimental Psychiatry 25(1), 49–59 (1994)CrossRefGoogle Scholar
  4. 4.
    Brown, E., Cairns, P.: A grounded investigation of game immersion. In: CHI 2004 Extended Abstracts on Human Factors in Computing Systems, pp. 1297–1300. ACM, New York (2004)CrossRefGoogle Scholar
  5. 5.
    Cheng, M., Gao, X., Gao, S., Xu, D.: Design and implementation of a brain-computer interface with high transfer rates. IEEE Transactions on Biomedical Engineering 49(10), 1181–1186 (2002)CrossRefGoogle Scholar
  6. 6.
    Cooper, R., Osselton, J., Shaw, J.: EEG technology. Butterworths, London (1969)Google Scholar
  7. 7.
    Farwell, L., Donchin, E.: Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalography and Clinical Neurophysiology 70(6), 510–523 (1988)CrossRefGoogle Scholar
  8. 8.
    Galán, F., Nuttin, M., Lew, E., Ferrez, P., Vanacker, G., Philips, J., Van Brussel, H., Millán, J.: An asynchronous and non-invasive brain-actuated wheelchair. In: 13th International Symposium on Robotics Research (2007) Google Scholar
  9. 9.
    van Gerven, M., Farquhar, J., Schaefer, R., Vlek, R., Geuze, J., Nijholt, A., Ramsey, N., Haselager, P., Vuurpijl, L., Gielen, S., Desain, P.: The brain–computer interface cycle. Journal of Neural Engineering 6(4), 041001 (2009)CrossRefGoogle Scholar
  10. 10.
    Hakvoort, G., Reuderink, B., Obbink, M.: Comparison of PSDA and CCA detection methods in a SSVEP-based BCI-system. Technical Report TR-CTIT-11-03, Centre for Telematics and Information Technology, University of Twente (2011) Google Scholar
  11. 11.
    Hoffmann, U., Vesin, J., Ebrahimi, T., Diserens, K.: An efficient P300-based brain-computer interface for disabled subjects. Journal of Neuroscience Methods 167(1), 115–125 (2008)CrossRefGoogle Scholar
  12. 12.
    Jennett, C., Cox, A., Cairns, P., Dhoparee, S., Epps, A., Tijs, T., Walton, A.: Measuring and defining the experience of immersion in games. International Journal of Human-Computer Studies 66(9), 641–661 (2008)CrossRefGoogle Scholar
  13. 13.
    Lansing, R., Schwartz, E., Lindsley, D.: Reaction time and EEG activation under alerted and nonalerted conditions. Journal of Experimental Psychology 58(1), 1–7 (1959)CrossRefGoogle Scholar
  14. 14.
    Lin, Z., Zhang, C., Wu, W., Gao, X.: Frequency Recognition Based on Canonical Correlation Analysis for SSVEP-Based BCIs. IEEE Transactions on Biomedical Engineering 53(12), 2610–2614 (2006)CrossRefGoogle Scholar
  15. 15.
    Lopez, M., Pelayo, F., Madrid, E., Prieto, A.: Statistical characterization of steady-state visual evoked potentials and their use in brain–computer interfaces. Neural Processing Letters 29(3), 179–187 (2009)CrossRefGoogle Scholar
  16. 16.
    Nijholt, A., Plass-Oude Bos, D., Reuderink, B.: Turning shortcomings into challenges: Brain-computer interfaces for games. Entertainment Computing 1(2), 85–94 (2009)CrossRefGoogle Scholar
  17. 17.
    Nijholt, A., Tan, D., Allison, B., et al.: Brain-Computer Interfaces for HCI and Games. In: CHI 2008 Extended Abstracts on Human Factors in Computing Systems, pp. 3925–3928. ACM, New York (2008)Google Scholar
  18. 18.
    Norman, D.: Emotion & design: attractive things work better. Interactions 9(4), 36–42 (2002)CrossRefGoogle Scholar
  19. 19.
    Pagulayan, R., Keeker, K., Wixon, D., Romero, R., Fuller, T.: User-centered design in games. In: The Human-Computer Interaction Handbook, pp. 883–906 (2002) Google Scholar
  20. 20.
    Picard, R.: Affective computing. The MIT press, Cambridge (2000)Google Scholar
  21. 21.
    Reilly, E.L.: EEG Recording and Operation of the Apparatus. In: Electroencephalography: Basic Principles, Clinical Applications and Related Fields, pp. 139–160. Lippincott Williams & Wilkins, Baltimore (1999)Google Scholar
  22. 22.
    Reynolds, C.W.: Flocks, herds and schools: A distributed behavioral model. In: SIGGRAPH 1987 Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques, pp. 25–34. ACM, New York (1987)CrossRefGoogle Scholar
  23. 23.
    Ruen Shan, L., Ibrahim, F., Moghavvemi, M.: Assessment of Steady-State Visual Evoked Potential for Brain Computer Communication. In: 3rd Kuala Lumpur International Conference on Biomedical Engineering 2006, pp. 352–354. Springer, Heidelberg (2006)Google Scholar
  24. 24.
    Volosyak, I., Cecotti, H., Gräser, A.: Impact of Frequency Selection on LCD Screens for SSVEP Based Brain-Computer Interfaces. In: Cabestany, J., Sandoval, F., Prieto, A., Corchado, J.M. (eds.) IWANN 2009. LNCS, vol. 5517, pp. 706–713. Springer, Heidelberg (2009)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2011

Authors and Affiliations

  • Gido Hakvoort
    • 1
  • Hayrettin Gürkök
    • 1
  • Danny Plass-Oude Bos
    • 1
  • Michel Obbink
    • 1
  • Mannes Poel
    • 1
  1. 1.Faculty EEMCSUniversity of TwenteEnschedeThe Netherlands

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