Cited by 30Gaze Tracking and Assistive TechnologyHuman-Automation Interaction and SafetyEmotion and Mood Recognition

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

PupilWare: towards pervasive cognitive load measurement using commodity devices

Rafiqi, Sohail, Wangwiwattana, Chatchai, Kim, Jasmine, Fernandez, Ephrem, Nair, Suku, Larson, Eric C.·2015·Proceedings of the 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments

Abstract

Cognitive load refers to the amount of effort required by an individual to process information. Dating back more than fifty years, the cognitive psychology community has conducted experiments showing that the cognitive load experienced by an individual can be measured using sub-millimeter fluctuations in their pupil size, assessed using medical grade infrared devices known as pupillometers, and more recently, infrared eye-trackers. However the cost and availability of these eye-trackers limits most pupil response measurement to laboratory settings. We argue that ubiquitously measuring pupillary response could transform the next generation of context aware computing applications---enabling computational devices to understand a user's current ability to process information, especially for users with cognitive disabilities. To this end, we present PupilWare, a system that analyzes pupil size changes through commodity cameras like those in a laptop. We evaluate PupilWare's ability to measure changes in pupil dilation using classic cognitive psychology experiments and validate its performance compared to infrared gaze trackers and medical grade pupillometers. We conclude that, in controlled conditions, PupilWare is as accurate as infrared eye-tracking for assessing task evoked cognitive load, though has problems with dark eyed individuals and eyelid occlusion.

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Crossref · 10.1145/2769493.2769506

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  • While some work showed feasible accuracy, other work argues that other modalities are superior.

    “While some work showed feasible accuracy [182,202], other work argues that other modalities are superior [87,201].”

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Research works printed but not linked: 38

  1. 10.1109/WMCSA.1994.16 · DOI
  2. 10.1109/MIS.2010.46 · DOI
  3. 10.1007/s00779-013-0716-5 · DOI
  4. 10.1109/WAINA.2014.88 · DOI
  5. 10.1016/j.cose.2006.05.004 · DOI
  6. 10.1007/11961635_9 · DOI
  7. Hu J., 2004, Proceedings of the first workshop on pervasive privacy security, privacy, and trust., 1
  8. Albu A. B., 2008, Veh. Symp., 25
  9. 10.1518/001872098779480479 · DOI
  10. 10.1037/h0026952 · DOI
  11. 10.1371/journal.pone.0056935 · DOI
  12. 10.1111/j.1469-8986.2008.00654.x · DOI · Paper page
  13. Stone B., 2004, Pupil Size and Mental Load," in 1st Adelaide Mental Life Conference
  14. 10.1177/1745691611427305 · DOI · Paper page
  15. 10.1016/j.ijpsycho.2003.12.001 · DOI
  16. 10.1126/science.132.3423.349 · DOI
  17. 10.1145/2071536.2071547 · DOI · Paper page
  18. Beatty J., 1982, Processing Load, and the Structure of Processing Resources," Psychological Bulletin
  19. 10.1111/j.1469-8986.1975.tb03068.x · DOI
  20. 10.1037/h0032456 · DOI
  21. 10.1111/j.1467-7687.2008.00805.x · DOI
  22. 10.1207/S15326985EP3801_6 · DOI · Paper page
  23. 10.1145/1344471.1344489 · DOI
  24. 10.1080/14640747108400239 · DOI
  25. Porta M., 2012, Eng. Educ. Conf. EDUCON
  26. Lafond D., 2014, Sixth Int. Conf. Adapt. Self-Adaptive Syst. Appl., no. c, 68
  27. Nijboer F., 2015, ScienceDirect Technology transfer of brain-computer interfaces as assistive technology : Barriers and opportunities, Ann. Phys. Rehabil. Med., 1
  28. 10.1016/j.cviu.2004.07.010 · DOI
  29. 10.1109/CVPR.2005.531 · DOI
  30. Ebisawa Y., 1994, Improved Video-Based Eye-Gaze Detection Method, IMTC, 1
  31. 10.1109/ICPR.2004.776 · DOI
  32. Keil A., 2010, WSCG, 4
  33. Long X., 2007, A High Speed Eye Tracking System with Robust Pupil Center Estimation Algorithm, Proceeding IEEE EMBS, 3331
  34. 10.1109/CVPR.2005.531 · DOI
  35. Fischler M. A., 1981, ACM, 24
  36. 10.1145/2578153.2578185 · DOI
  37. Timm F., 2011, Accurate Eye Center Localisation by means of gradient," VISAPP
  38. Zugal S., 2014, Low-Cost Eye-Trackers: User for Information Systems Research?

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Metadata

Authors
Rafiqi, S., Wangwiwattana, C., Kim, J., Fernandez, E., Nair, S., & Larson, E. C.
Affiliations
  • Southern Methodist University (US)
  • University of Texas, San Antonio, TX
Venue
Proceedings of the 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments
Publisher
ACM
Published
2015-07
Pages
1-8
OpenAlex
W1987995821
Cited by
30
References
2
Citations by year
2026: 4 · 2025: 3 · 2024: 4 · 2023: 3 · 2022: 2 · 2021: 4 · 2019: 1 · 2018: 3 · 2017: 2 · 2016: 3 · 2015: 1
FWCI
2.27
Type
conference paper
Language
en
Open access
closed
Locations
International Conference on PErvasive Technologies Related to Assistive Environments (PETRA) (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
  • Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
  • Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
Keywords
pupil dilation, cognitive load, pupillometry, infrared eye tracking, context-aware computing, cognitive disability, eyelid occlusion

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