Performance Evaluation of the Gazepoint GP3 Eye Tracking Device Based on Pupil Dilation

  • Pujitha MannaruEmail author
  • Balakumar Balasingam
  • Krishna Pattipati
  • Ciara Sibley
  • Joseph T. Coyne
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10284)


Eye tracking is considered one of the most salient methods to study the cognitive demands of humans in human computer interactive systems, due to the unobtrusiveness, flexibility and the development of inexpensive eye trackers. In this work, we evaluate the applicability of these low cost eyetrackers to study pupillary response to varying memory loads and luminance conditions. Specifically, we examine a low-cost eye tracker, the Gazepoint GP3, and objectively evaluate its ability to differentiate pupil dilation metrics under different cognitive loads and luminance conditions. The classification performance is computed in the form of a receiver operating characteristic (ROC) curve and the results indicate that Gazepoint provides a reliable eye tracker to human computer interaction applications requiring pupil dilation studies.


Low-cost eye trackers Eye tracker performance Gazepoint Pupil dilation Memory load TEPR Power spectral density 



The authors would like to thank Dr. Jeffrey Morrison and the Command Decision Making (CDM) program at the U.S. Office of Naval Research and Department of Defense High Performance Computing Modernization Program for supporting this work. In addition, the authors would like to thank the symposium organizers for their encouragement of this work. This research was funded by the U.S. Office of Naval Research and the Department of Defense under contracts #N00014-12-1-0238, #N00014-16-1-2036 and #HPCM034125HQU.


  1. 1.
    Just, M.A., Carpenter, P.A.: The intensity dimension of thought: pupillometric indices of sentence processing. Can. J. Exp. Psychol./Revue canadienne de psychologie expérimentale 47(2), 310 (1993)CrossRefGoogle Scholar
  2. 2.
    Palinko, O., Kun, A.L., Shyrokov, A., Heeman, P.: Estimating cognitive load using remote eye tracking in a driving simulator. In: Proceedings of 2010 Symposium on Eye-Tracking Research and Applications, pp. 141–144. ACM (2010)Google Scholar
  3. 3.
    Odenheimer, G., Funkenstein, H., Beckett, L., Chown, M., Pilgrim, D., Evans, D., Albert, M.: Comparison of neurologic changes in’successfully aging’persons vs the total aging population. Arch. Neurol. 51(6), 573–580 (1994)CrossRefGoogle Scholar
  4. 4.
    Ekman, I.M., Poikola, A.W., Mäkäräinen, M.K.: Invisible eni: using gaze and pupil size to control a game. In: CHI 2008 Extended Abstracts on Human Factors in Computing Systems, pp. 3135–3140. ACM (2008)Google Scholar
  5. 5.
    Ren, P., Barreto, A., Gao, Y., Adjouadi, M.: Affective assessment of computer users based on processing the pupil diameter signal. In: Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE, pp. 2594–2597. IEEE (2011)Google Scholar
  6. 6.
    Zugal, S., Pinggera, J.: Low–cost eye–trackers: useful for information systems research? In: Iliadis, L., Papazoglou, M., Pohl, K. (eds.) CAiSE 2014. LNBIP, vol. 178, pp. 159–170. Springer, Cham (2014). doi: 10.1007/978-3-319-07869-4_14 Google Scholar
  7. 7.
    Dalmaijer, E.: Is the low-cost eyetribe eye tracker any good for research? Technical report, PeerJ PrePrints (2014)Google Scholar
  8. 8.
    Ooms, K., Dupont, L., Lapon, L., Popelka, S.: Accuracy and precision of fixation locations recorded with the low-cost eye tribe tracker in different experimental setups. J. Eye Mov. Res. 8(1) (2015)Google Scholar
  9. 9.
    Ferhat, O., Vilariño, F.: Low cost eye tracking. Comput. Intell. Neurosci. 2016, 17 (2016)CrossRefGoogle Scholar
  10. 10.
    Coyne, J., Sibley, C.: Investigating the use of two low cost eye tracking systems for detecting pupillary response to changes in mental workload. In: Proceedings of Human Factors and Ergonomics Society Annual Meeting, vol. 60, pp. 37–41. SAGE Publications (2016)Google Scholar
  11. 11.
    Funke, G., Greenlee, E., Carter, M., Dukes, A., Brown, R., Menke, L.: Which eye tracker is right for your research? Performance evaluation of several cost variant eye trackers. In: Proceedings of Human Factors and Ergonomics Society Annual Meeting, vol. 60, pp. 1240–1244. SAGE Publications (2016)Google Scholar
  12. 12.
    Gibaldi, A., Vanegas, M., Bex, P.J., Maiello, G.: Evaluation of the Tobii EyeX eye tracking controller and Matlab toolkit for research. Behav. Res. Methods 1–24 (2016)Google Scholar
  13. 13.
    Janthanasub, V., Meesad, P.: Evaluation of a low-cost eye tracking system for computer input. King Mongkuts Univ. Technol. North Bangk. Int. J. Appl. Sci. Technol. 8(3), 185–196 (2015)Google Scholar
  14. 14.
    Causse, M., Sénard, J.-M., Démonet, J.F., Pastor, J.: Monitoring cognitive and emotional processes through pupil and cardiac response during dynamic versus logical task. Appl. Psychophysiol. Biofeedback 35(2), 115–123 (2010)CrossRefGoogle Scholar
  15. 15.
    Mannaru, P., Balasingam, B., Pattipati, K., Sibley, C., Coyne, J.: Cognitive context detection in UAS operators using pupillary measurements. In: SPIE Defense+ Security, p. 98510Q. International Society for Optics and Photonics (2016)Google Scholar
  16. 16.
    Mandrick, K., Peysakhovich, V., Rémy, F., Lepron, E., Causse, M.: Neural and psychophysiological correlates of human performance under stress and high mental workload. Biol. Psychol. 121, 62–73 (2016)CrossRefGoogle Scholar
  17. 17.
    Beatty, J.: Task-evoked pupillary responses, processing load, and the structure of processing resources. Psychol. Bull. 91(2), 276 (1982)CrossRefGoogle Scholar
  18. 18.
    Peysakhovich, V., Causse, M., Scannella, S., Dehais, F.: Frequency analysis of a task-evoked pupillary response: luminance-independent measure of mental effort. Int. J. Psychophysiol. 97(1), 30–37 (2015)CrossRefGoogle Scholar
  19. 19.
    Kahneman, D., Beatty, J.: Pupil diameter and load on memory. Science 154(3756), 1583–1585 (1966)CrossRefGoogle Scholar
  20. 20.
    Tryon, W.W.: Pupillometry: a survey of sources of variation. Psychophysiology 12(1), 90–93 (1975)CrossRefGoogle Scholar
  21. 21.
    Taptagaporn, S., Saito, S.: How display polarity and lighting conditions affect the pupil size of VDT operators. Ergonomics 33(2), 201–208 (1990)CrossRefGoogle Scholar
  22. 22.
    Goldinger, S.D., Papesh, M.H.: Pupil dilation reflects the creation and retrieval of memories. Curr. Dir. Psychol. Sci. 21(2), 90–95 (2012)CrossRefGoogle Scholar
  23. 23.
    Winn, B., Whitaker, D., Elliott, D.B., Phillips, N.J.: Factors affecting light-adapted pupil size in normal human subjects. Investig. Ophthalmol. Vis. Sci. 35(3), 1132–1137 (1994)Google Scholar
  24. 24.
    Peysakhovich, V., Vachon, F., Dehais, F.: The impact of luminance on tonic and phasic pupillary responses to sustained cognitive load. Int. J. Psychophysiol. 112, 40–45 (2017)CrossRefGoogle Scholar
  25. 25.
  26. 26.
    Beatty, J., Lucero-Wagoner, B.: The pupillary system. Handb. Psychophysiol. 2, 142–162 (2000)Google Scholar
  27. 27.
    Gardner, R.M., Beltramo, J.S., Krinsky, R.: Pupillary changes during encoding, storage, and retrieval of information. Percept. Mot. Skills 41(3), 951–955 (1975)CrossRefGoogle Scholar
  28. 28.
    MATLAB: R2016a. The MathWorks Inc., Natick (2016)Google Scholar
  29. 29.
    Papesh, M.H., Goldinger, S.D., Hout, M.C.: Memory strength and specificity revealed by pupillometry. Int. J. Psychophysiol. 83(1), 56–64 (2012)CrossRefGoogle Scholar
  30. 30.
    Pearson, R.K.: Outliers in process modeling and identification. IEEE Trans. Control Syst. Technol. 10(1), 55–63 (2002)CrossRefGoogle Scholar
  31. 31.
    Nakayama, M., Shimizu, Y.: Frequency analysis of task evoked pupillary response and eye-movement. In: Proceedings of 2004 Symposium on Eye Tracking Research Applications, pp. 71–76. ACM (2004)Google Scholar
  32. 32.
    Fawcett, T.: An introduction to ROC analysis. Pattern Recogn. Lett. 27(8), 861–874 (2006)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Pujitha Mannaru
    • 1
    Email author
  • Balakumar Balasingam
    • 1
  • Krishna Pattipati
    • 1
  • Ciara Sibley
    • 2
  • Joseph T. Coyne
    • 2
  1. 1.Department of Electrical and Computer EngineeringUniversity of ConnecticutStorrsUSA
  2. 2.Warfighter Human Systems Integration LabNaval Research LaboratoryWashington DCUSA

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