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 degree and a further degradation over time at a rate of 0.13 degree. month-1. The overall median accuracy was 1.00 degree (50.9 pixels) and the overall median precision was 0.16 degree (8.3 pixels). The results from the ultrasonography setting show a decrease of accuracy of 0.16 degree 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.

IEEE Transactions on Cybernetics


 title = {Evaluation of Gaze Tracking Calibration for Longitudinal Biomedical Imaging Studies},
 author = {Chatelain, Pierre and Sharma, Harshita and Drukker, Lior and Papageorghiou, Aris T. and Noble, J. Alison},
 doi = {10.1109/TCYB.2018.2866274},
 issn = {2168-2275},
 journal = {IEEE Transactions on Cybernetics},
 number = {1},
 pages = {153--163},
 volume = {50},
 year = {2020}