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| Content Provider | ACM Digital Library |
|---|---|
| Author | Fekety, Drea K. Kun, Andrew L. Schmidt, Albrecht Pfleging, Bastian |
| Abstract | In this paper, we present a proof-of-concept approach to estimating mental workload by measuring the user's pupil diameter under various controlled lighting conditions. Knowing the user's mental workload is desirable for many application scenarios, ranging from driving a car, to adaptive workplace setups. Typically, physiological sensors allow inferring mental workload, but these sensors might be rather uncomfortable to wear. Measuring pupil diameter through remote eye-tracking instead is an unobtrusive method. However, a practical eye-tracking-based system must also account for pupil changes due to variable lighting conditions. Based on the results of a study with tasks of varying mental demand and six different lighting conditions, we built a simple model that is able to infer the workload independently of the lighting condition in 75% of the tested conditions. |
| Starting Page | 5776 |
| Ending Page | 5788 |
| Page Count | 13 |
| File Format | |
| ISBN | 9781450333627 |
| DOI | 10.1145/2858036.2858117 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-05-07 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Task-evoked pupillary response Adaptive user interfaces Eye-tracking Lighting Compensation of pupillary light reflex Cognitive workload Estimation of mental workload Psychophysiology |
| Content Type | Text |
| Resource Type | Article |
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