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References

This tool

The methods implemented here:

  • Pignoni, G., Komandur, S., & Volden, F. (2021). Accounting for effects of variation in luminance in pupillometry for field measurements of cognitive workload. IEEE Sensors Journal. doi:10.1109/JSEN.2020.3038291. The lux sensor method (eq. 5–8) used for the glasses (Pupil Core, Neon, Glasses 3).
  • Pignoni, G., Grandi, F., & Peruzzini, M. Toward Reliable Pupillometry in Extended Reality Environments: A Video-Based Pipeline for Isolating Cognitive Workload from Pupil Data. Manuscript in preparation, not yet published; the method may change before publication. Display photometric calibration, two-area luminance and the calibration sequence used for the Varjo XR-4. Pages that refer to "the Varjo manuscript" mean this text.

Related publications using the tool and its lux sensor:

  • Pignoni, G., & Komandur, S. (2019). Development of a quantitative evaluation tool of cognitive workload in field studies through eye tracking. Lecture Notes in Computer Science, 11571. doi:10.1007/978-3-030-22507-0_9
  • Pignoni, G., Hareide, O. S., Komandur, S., & Volden, F. (2019). Trial application of pupillometry for a maritime usability study in field conditions. Necesse, 4. NTNU Open
  • Streilein, T., Komandur, S., Pignoni, G., Volden, F., Lunde, P., & Mjelde, F. V. (2020). Maritime navigation: characterizing collaboration in a high-speed craft navigation activity. Communications in Computer and Information Science, 1224. PDF
  • Pignoni, G., & Komandur, S. (2022). Practical challenges in using eye trackers in the field. In Human-Automation Interaction: Mobile Computing (pp. 653–662). Springer. doi:10.1007/978-3-031-10788-7_37

Models

  • Watson, A. B., & Yellott, J. I. (2012). A unified formula for light-adapted pupil size. Journal of Vision, 12(10):12.
  • Stanley, P. A., & Davies, A. K. (1995). The effect of field of view size on steady-state pupil diameter. Ophthalmic & Physiological Optics, 15(6), 601–603.
  • Eckert, M., Robotham, T., Habets, E. A. P., & Rummukainen, O. S. (2022). Pupillary light reflex correction for robust pupillometry in virtual reality. Proc. ACM Comput. Graph. Interact. Tech., 5(2), Article 18. doi:10.1145/3530798. Per-participant mapping functions from calibration sequences (6 s steps in pseudo-random order proved most robust) and luminance from a weighted average of the fixation area and the background.

Data formats

  • Varjo Base eye tracking recorder output (checked against an April 2026 export).
  • Pupil Labs, Pupil Core raw data exporter (Pupil Player).
  • Pupil Labs, Neon recording format and pl-neon-recording.