Abstract
To analyze eye-tracking data the viewed image is often divided into areas of interest (AOI). However, the temporal dynamics of eye movements towards the AOI is often lost either in favor of summary statistics (e.g., proportion of fixations or dwell time) or is significantly reduced by "binning" the data and computing the same summary statistic over each time bin. This paper introduces SPLOT: smoothed proportion of looks over time method for analyzing the eye movement dynamics across AOI. SPLOT comprises of a complete workflow, from visualization of the time-course to performing statistical analysis on it using cluster-based permutation testing. The possibilities of SPLOT are illustrated by applying it to an existing dataset of eye movements of radiologists diagnosing a chest X-ray.
| Original language | English |
|---|---|
| Title of host publication | ETRA 2020 Short Papers |
| Subtitle of host publication | ACM Symposium on Eye Tracking Research and Applications |
| Editors | Stephen N. Spencer |
| Publisher | Association for Computing Machinery |
| Pages | 1-4 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781450371346 |
| DOIs | |
| Publication status | Published - Jun 2020 |
| Event | 2020 ACM Symposium on Eye Tracking Research and Applications, ETRA 2020 - Stuttgart, Germany Duration: 2 Jun 2020 → 5 Jun 2020 |
Publication series
| Name | Eye Tracking Research and Applications Symposium (ETRA) |
|---|
Conference
| Conference | 2020 ACM Symposium on Eye Tracking Research and Applications, ETRA 2020 |
|---|---|
| Country/Territory | Germany |
| City | Stuttgart |
| Period | 2/06/20 → 5/06/20 |
Funding
This research was supported by an Open Area Research Grant from the Netherlands Organization for Scientific Research to Artem Belopolsky: ORA 464-15-193.
Keywords
- Area Of Interest analysis
- Cluster-based permutation
- Eye movement dynamics
- Eye Tracking
- Proportion of looks over time