EasyEyes: Crowded Dynamic Fixation for Online Psychophysics.

Abstract

Online vision testing enables efficient data collection from diverse participants but requires accurate fixation. Fixation accuracy is traditionally ensured by using a camera to track gaze. That works well in the lab, but tracking during online testing with a built-in webcam is not yet sufficiently precise. Kurzawski, Pombo, et al. (2023) introduced a fixation task that improves fixation through hand-eye coordination, requiring participants to track a moving crosshair with a mouse-controlled cursor. This dynamic fixation task greatly reduces peeking at peripheral targets relative to a stationary fixation task, but does not eliminate it. Here, we enhance fixation further by leveraging "crowding," adding clutter around the fixation mark-a method we call crowded dynamic fixation. We assessed fixation accuracy during peripheral threshold measurement. Relative to the RMS gaze error during the stationary fixation task, dynamic fixation error was 61%, while crowded dynamic fixation error was only 47%. With a 1.5° tolerance, peeking occurred on 9% of trials with stationary fixation, 4% with dynamic fixation, and 0% with crowded dynamic fixation. This improvement eliminated implausibly low peripheral thresholds, likely by preventing peeking. We conclude that crowded dynamic fixation enables accurate gaze control for online testing.