bioRxiv · 10.1101/2023.06.12.544554
Quantitative comparison of a mobile, tablet-based and two stationary, video-based eye-trackers
Abstract
AbstractThe analysis of eye-movements is a non-invasive, reliable and fast method to detect and quantify brain (dys-)functions. Here, we investigated the performance of two novel eye-trackers: the Thomas-Oculus-Motus-research mobile (TOM-rm) and the TOM-research stationary (TOM-rs) and compared it with the performance of a well-established video-based eye-tracker, i.e., the EyeLink 1000 (EL). The TOM-rm is a fully integrated, tablet-based mobile device that presents visual stimuli and records head-unrestrained eye-movements at 30Hz without additional infrared (IR) illumination. The TOM-rs is a stationary, video-based eye-tracker that records eye-movements at either high spatial or high temporal resolution. We compared the performance of all three eye-trackers in two different behavioral tasks: pro- and anti-saccade and free viewing. We collected data from human subjects while running all three eye-tracking devices in parallel. Parameters requiring a high spatial or temporal resolution (e.g., saccade latency or gain), as derived from the data, differed significantly between the EL and the TOM-rm in the pro- and anti-saccade task. In the free viewing task, larger noise and the lower frame rate of the TOM-rm caused deviations of the results with respect to the EL. Differences between results derived from the TOM-rs and the EL were most likely due to experimental conditions, which could not be optimized for both systems simultaneously. We conclude that the TOM-rm can be used for measuring eye-movements reliably at comparably low spatial and temporal resolution. The TOM-rs, on the other hand, can provide high-resolution oculomotor data at least on a par with an established reference system.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Koenig, A., Bremmer, F., Dowiasch, S.. 2023-06-12. Quantitative comparison of a mobile, tablet-based and two stationary, video-based eye-trackers. https://doi.org/10.1101/2023.06.12.544554
Cite the original work for its findings. Save a collection to share your selection of sources.