Significance of Pupil Diameter Measurements for the Assessment of Affective State in Computer Users

  • Armando Barreto
  • Jing Zhai
  • Naphtali Rishe
  • Ying Gao


The need to provide computers with the ability to distinguish the affective state of their users is a major requirement for the practical implementation of Affective Computing concepts. The determination of the affective state of a computer user from the measurement of some of his/her physiological signals is a promising avenue towards that goal. In addition to the monitoring of signals typically analyzed for affective assessment, such as the Galvanic Skin Response (GSR) and the Blood Volume Pulse (BVP), other physiological variables, such as the Pupil Diameter (PD) may be able to provide a way to assess the affective state of a computer user, in real-time. This paper studies the significance of pupil diameter measurements towards differentiating two affective states (stressed vs. relaxed) in computer users performing tasks designed to elicit those states in a predictable sequence. Specifically, the paper compares the discriminating power exhibited by the pupil diameter measurement to those of other single-index detectors derived from simultaneously acquired signals, in terms of their Receiver Operating Characteristic (ROC) curves.


Receiver Operating Characteristic Receiver Operating Characteristic Curve Affective State True Positive Rate Computer User 
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  1. [1]
    Picard, R.W. 1997. Affective computing. MIT Press, Cambridge, Mass.Google Scholar
  2. [2]
    Partala, T., Surakka, V. 2003. Pupil size variation as an indication of affective processing. Int. J. of Human-Computer Studies 59:185-198CrossRefGoogle Scholar
  3. [3]
    Beatty, J., Lucero-wagoner, B. 2000. The Pupillary System. In: Handbook of Psychophysiology. J.T. Cacioppo, L.G. Tassinary, and G.G. Berntson, editors. pp. 142-162. Cambridge University PressGoogle Scholar
  4. [4]
    Hess, E.H. 1975. The tell-tale eye : how your eyes reveal hidden thoughts and emotions. Van Nostrand Reinhold, New YorkGoogle Scholar
  5. [5]
    Grings, W.W., Dawson, M.E. 1978. Emotions and Bodily Responses A psychophysiological Approach. Academic Press, Inc.Google Scholar
  6. [6]
    Stroop, J.R. 1935. Interference in serial verbal reactions. Journal of Experimental Psychology 18:643-661CrossRefGoogle Scholar
  7. [7]
    Renaud, P. and Blondin, J.-P., “The stress of Stroop performance: physiological and emotional responses to color-word interference, task pacing, and pacing speed,” International Journal of Psychophysiology, vol. 27, pp. 87-97, 1997.CrossRefGoogle Scholar
  8. [8]
    Stern, R.M., Ray, W.J., Quigley, K.S. 2001. Psychophysiological Recording. Oxford University Press.Google Scholar
  9. [9]
    Barreto, A. and Zhai, J., “Physiological Instrumentation for Real-time Monitoring of Affective State of Computer Users,” WSEAS Transactions on Circuits and Systems, vol. 3, pp. 496-501, 2003.Google Scholar
  10. [10]
    Usui, S. and Amidror, I., “Digital Low-Pass Differentiation for Biological Signal Processing,” IEEE Trans. BME, 29: 686-693, 1982.Google Scholar
  11. [11]
    Zhai J., and Barreto A., “Stress Detection in Computer Users Through Noninvasive Monitoring of Physiological Signals “, Biomedical Science Instrumentation, vol. 42, pp. 495-500, 2006..Google Scholar
  12. [12]
    Zhai, J., and Barreto, A., “Stress Detection in Computer Users Based on Digital Signal Processing of Noninvasive Physiological Variables”, Proceedings of the 28th IEEE EMBS Annual International Conference New York City, USA, Aug 30-Sept 3, 2006, pp. 1355 – 1358.Google Scholar
  13. [13]
    Zhai, J., and Barreto, A., “Stress Recognition Using Non-invasive Technology”, Proceedings 19th Int. Florida Artificial Intelligence Research Society Conference (FLAIRS 2006), pp. 395 – 400, 2006.Google Scholar

Copyright information

© Springer 2007

Authors and Affiliations

  • Armando Barreto
    • 1
  • Jing Zhai
    • 1
  • Naphtali Rishe
    • 2
  • Ying Gao
    • 1
  1. 1.Electrical and Computer Engineering DepartmentFlorida International UniversityMiamiUSA
  2. 2.School of Computer and Information SciencesFlorida International UniversityMiamiUSA

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