Evaluation of Gaze Tracking Calibration for Longitudinal Biomedical Imaging Studies

Gaze tracking is a promising technology for studying the visual perception of clinicians during image-based medical exams. It could be used in longitudinal studies to analyze their perceptive process, explore human-machine interactions, and develop innovative computer-aided imaging systems. However, using a remote eye tracker in an unconstrained environment and over time periods of weeks requires a certain guarantee of performance to ensure that collected gaze data are fit for purpose. We report the results of evaluating eye tracking calibration for longitudinal studies. First, we tested the performance of an eye tracker on a cohort of 13 users over a period of one month. For each participant, the eye tracker was calibrated during the first session. The participants were asked to sit in front of a monitor equipped with the eye tracker, but their position was not constrained. Second, we tested the performance of the eye tracker on sonographers positioned in front of a cart-based ultrasound scanner. Experimental results show a decrease of accuracy between calibration and later testing of 0.30° and a further degradation over time at a rate of 0.13°. month^-1. The overall median accuracy was 1.00° (50.9 pixels) and the overall median precision was 0.16° (8.3 pixels). The results from the ultrasonography setting show a decrease of accuracy of 0.16° between calibration and later testing. This slow degradation of gaze tracking accuracy could impact the data quality in long-term studies. Therefore, the results we present here can help in planning such long-term gaze tracking studies.

I. Introduction

Gaze tracking is the process of determining one’s point-of-gaze as a temporal sequence of coordinates. Spatially registering the points-of-gaze to a visual stimulus displayed on a monitor requires a calibration which depends on several factors related to the subject (physiological properties, presence of sight correction apparatus) or the environment (illumination, position of the monitor) [1]. While controlled cross-subject and cross-device comparative studies of gaze tracking accuracy are available in [2], these do not provide any information on whether the accuracy may degrade in time. In addition, vendor-provided performance information is an estimate assuming a specific use context [e.g., desktop-based human–computer interaction (HCI)].