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PupilWare: towards pervasive cognitive load measurement using commodity devices
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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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].”
From A Survey on Measuring Cognitive Workload in Human-Computer Interaction (2023) · cites this paper as [182]
Citations
Cites
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Iqbal, S. T., Zheng, X. S., & Bailey, B. P. (2004) · CHI '04 Extended Abstracts on Human Factors in Computing Systems · doi:10.1145/985921.986094 · Cited by 317
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Sorted by citations
A Survey on Measuring Cognitive Workload in Human-Computer Interaction
Kosch, T., Karolus, J., Zagermann, J., Reiterer, H., Schmidt, A., & Woźniak, P. W. (2023) · ACM Computing Surveys · doi:10.1145/3582272 · Cited by 304
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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