Abstract
We validate a novel algorithm to detect saccades from raw data obtained during walking from a mobile infra-red eye-tracking device. The algorithm was based on a velocity threshold detection method, which excluded artefacts such as blinks and flickers using specific criteria. Mobile infra-red eye-tracking was performed with a group of healthy older adults (n=5) and Parkinson's disease (n=5) subjects. Saccades determined from raw eye tracker data obtained during walking using the algorithm were compared to a ground truth dataset defined as frame-by-frame visual inspection of raw eye-tracking videos. 100 trials from 10 subjects were analyzed and compared. The algorithm was highly reliable when compared to the ground truth (ICC(2,1) = 0.94), with an overall correct saccade detection percentage of 85%. This provides a simple yet robust algorithm for the analysis of mobile eye-tracking data.
| Original language | English |
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| Title of host publication | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 |
| Publisher | IEEE |
| Pages | 5739-5742 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781424479290 |
| DOIs | |
| Publication status | Published - 6 Nov 2014 |
| Externally published | Yes |
| Event | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States Duration: 26 Aug 2014 → 30 Aug 2014 |
Conference
| Conference | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 |
|---|---|
| Country/Territory | United States |
| City | Chicago |
| Period | 26/08/14 → 30/08/14 |