Measuring cognitive load during visual tasks by combining pupillometry and eye tracking
Abstract/Contents
- Abstract
- Visualizations and visual interfaces can provide the means to analyze and communicate complex information, but such interfaces often overwhelm or confuse their users. Evaluating an interfaces's propensity to overload users requires the ability to assess cognitive load. Changes in cognitive load cause very small dilations of the pupils. In controlled settings, high-precision pupil measurements can be used to detect small differences in cognitive load at time scales shorter than one second. However, cognitive pupillometry has been generally limited to experiments using auditory stimuli and a blank visual field, because the pupils' responsiveness to changes in brightness and other visual details interferes with load-induced pupil dilations. In this dissertation, I present several improvements in methods for measuring cognitive load using pupillary dilations. First, I extend the set of eye tracking equipment validated for cognitive pupillometry, by determining the pupillometric precision of a remote-camera eye tracker and using remote camera equipment to replicate classic cognitive pupillometry experiments performed originally using head-mounted cameras. Second, I extend the applicability of cognitive pupillometry in visual tasks by developing fixation-aligned averaging methods to to handle the unpredictability of visual attention, and by demonstrating the measurement of cognitive load during visual search and map reading. I describe the methods used to accomplish these results, including experimental protocols and data processing methods to control or correct for various non-cognitive pupillary reflexes and methods for combining pupillometry with eye tracking. I present and discuss a new finding of a cognitive load advantage to visual presentation of simple arithmetic and memorization tasks.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2010 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Klingner, Jeffrey Michael |
|---|---|
| Associated with | Stanford University, Computer Science Department |
| Primary advisor | Hanrahan, P. M. (Patrick Matthew) |
| Thesis advisor | Hanrahan, P. M. (Patrick Matthew) |
| Thesis advisor | Klemmer, Scott |
| Thesis advisor | Tversky, Barbara |
| Advisor | Klemmer, Scott |
| Advisor | Tversky, Barbara |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Jeffrey Michael Klingner. |
|---|---|
| Note | Submitted to the Department of Computer Science. |
| Thesis | Thesis (Ph. D.)--Stanford University, 2010. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2010 by Jeffrey Michael Klingner
- License
- This work is licensed under a Creative Commons Attribution Non Commercial Share Alike 3.0 Unported license (CC BY-NC-SA).
Also listed in
Loading usage metrics...