Comparing the Levels of Frustration between an Eye-Tracker and a Mouse: A Pilot Study

  • Hildegardo Noronha
  • Ricardo Sol
  • Athanasios Vourvopoulos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7946)


This paper tries to identify increases in user frustration when using Eye-Tracking devices as compared to common interfacing devices like a standard mouse. For this, we used an electroencephalograph (EEG) to measure frustration levels while users navigated within a maze using each of the referred devices. Results from the analysis performed on the EEG data indicate that Eye-tracking has the same amount of frustration as a standard mouse for common mouse tracking tasks. In addition, a correlation between the user’s reported frustration and the extracted EEG data could not be found rendering the above result virtually invalid. The users’ self-reported frustration lends support to our hypothesis but it still is not statistically significant and hence does not confirm the hypothesis.


Human Computer Interaction Natural User Interfaces Eye-Tracker Mouse Electroencephalography 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Zuchowski, A.: Eye Tracking Methodology: Theory and Practice. Springer, Berlin (2003)CrossRefGoogle Scholar
  2. 2.
    Carew, T.J.: Behavioral Neurobiology: The Cellular Organization of Natural Behavior. Sinauer Associates Inc. (2004)Google Scholar
  3. 3.
    Gevins, A., Zeitlin, G., Yingling, C., Doyle, J., Dedon, M., Schaffer, R., Roumasset, J., Yeager, C.: EEG patterns during cognitive tasks. I. Methodology and analysis of complex behaviors. Electroencephalography and Clinical Neurophysiology 47(6), 693–703 (1979)CrossRefGoogle Scholar
  4. 4.
    Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Braincomputer interfaces for communication and control, Clinical neurophysiology? Official Journal of the International Federation of Clinical Neurophysiology 113, 767–791 (2002)CrossRefGoogle Scholar
  5. 5.
    Lecuyer, A., Lotte, F., Reilly, R.B., Leeb, R., Hirose, M., Slater, M.: Brain-Computer Interfaces, Virtual Reality, and Videogames. Computer 41, 66–72 (2008)CrossRefGoogle Scholar
  6. 6.
    Loudin, J.D., Simanovskii, D.M., Vijayraghavan, K., Sramek, C.K., Butterwick, A.F., Huie, P., McLean, G.Y., Palanker, D.V.: Optoelectronic retinal prosthesis: system design and performance. J. Neural Eng. 4(1), S72–S84 (2007)Google Scholar
  7. 7.
    Emotiv | EEG System | Electroencephalography, (accessed: December 16, 2012)
  8. 8.
    Taylor, G.S., Schmidt, C.: Empirical Evaluation of the Emotiv EPOC BCI Headset for the Detection of Mental Actions. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 56(1), pp. 193–197 (September 2012)Google Scholar
  9. 9.
    Goldberg, B., Brawner, K.W., Holden, H.K.: Efficacy of Measuring Engagement during Computer-Based Training with Low-Cost Electroencephalogram (EEG) Sensor Outputs. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 56(1), pp. 198–202 (September 2012)Google Scholar
  10. 10.
    SensoMotoric Instruments GmbH Gaze and Eye Tracking Systems Applications Neuromarketing, (accessed: December 16, 2012)
  11. 11.
    Klem, G.H., Lders, H.O., Jasper, H.H., Elger, C.: The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology, Electroencephalogr. Clin. Neurophysiol. Suppl. 52, 3–6 (1999)Google Scholar
  12. 12.
    Hart, S.G.: NASA-Task Load Index (NASA-TLX); 20 Years Later. In: Proceedings of the Human Factors and Ergonomics Society 50th Annual Meeting, pp. 904–908. HFES, Santa Monica (2006)Google Scholar
  13. 13.
    Ashmore, M., Duchowski, A.T., Shoemaker, G.: Efficient Eye Pointing with a Fisheye Lens. In: Proceedings of Graphics interface 2005, ACM International Conference Proceeding Series, vol. 112, pp. 203–210 (2005)Google Scholar
  14. 14.
    Jacob, R.J.K.: What You Look at is What You Get: Eye Movement-Based Interaction Techniques. In: Proc. CHI 1990, pp. 11–18. ACM Press (1990)Google Scholar
  15. 15.
    Zhai, S., Morimoto, C., Ihde, S.: Manual and gaze input cascaded (MAGIC) pointing. In: Proc. of CHI 1999, pp. 246–253. ACM (1999)Google Scholar
  16. 16.
    Salvucci, D.D., Anderson, J.R.: Intelligent Gaze-Added Interfaces. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2000, pp. 273–280. ACM Press (2000)Google Scholar
  17. 17.
    McGuffin, M., Balakrishnan, R.: Acquisition of Expanding Targets. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems CHI 2002, pp. 57–64. ACM Press (2002)Google Scholar
  18. 18.
    Miniotas, D., Špakov, O., MacKenzie, I.S.: Eye Gaze Interaction with Expanding Targets. In: CHI 2004 Extended Abstracts on Human Factors in Computing Systems, pp. 1255–1258. ACM Press (2005)Google Scholar
  19. 19.
    Kumar, M., Paepcke, A., Winograd, T.: EyePoint: Practical Pointing and Selection Using Gaze and Keyboard. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems CHI 2007, pp. 421–430. ACM Press (2007)Google Scholar
  20. 20.
    Tobii Technology, Tobii TX300 Eye Tracker Users Manual (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hildegardo Noronha
    • 1
  • Ricardo Sol
    • 1
  • Athanasios Vourvopoulos
    • 1
  1. 1.Madeira Interactive Technologies InstituteUniversity of MadeiraMadeiraPortugal

Personalised recommendations