TREYESCAN: configuration of an eye tracking test for the measurement of compensatory eye movements in patients with visual field defects.

The Traffic Eye Scanning and Compensation Analyzer (TREYESCAN) is introduced as an innovative eye tracking test designed to measure compensatory eye movements in individuals with visual field defects. The primary objective of the test is to quantitatively assess and analyze the compensatory eye movements employed by patients with visual field defects while viewing videos of various traffic scenes from the viewpoint of a driver of a passenger car. The filming process involved capturing a wide range of driving conditions and hazards, aiming to replicate real-world scenarios. Specific dynamic areas of interest within these scenes were selected and assessed by a panel of experts on medical and practical fitness to drive. Pilot measurements were conducted on a sample of 20 normally-sighted individuals during two different measurement sessions. The results provide valuable insights into how individuals without visual impairment view the dynamic scenes presented in the test. Moving forward, the TREYESCAN will be used in a case-control study involving glaucoma patients and control subjects, with the goal of further investigating and understanding the mechanisms employed by individuals with glaucoma to compensate for their visual field defects.

A toolkit for wide-screen dynamic area of interest measurements using the Pupil Labs Core Eye Tracker.

Eye tracking measurements taken while watching a wide field screen are challenging to perform. Commercially available remote eye trackers typically do not measure more than 35 degrees in eccentricity. Analysis software was developed using the Pupil Core Eye Tracking data to analyze viewing behavior under circumstances as natural as possible, on a 1.55-m-wide screen allowing free head movements. Additionally, dynamic area of interest (AOI) analyses were performed on data of participants viewing traffic scenes. A toolkit was created including software for simple allocation of dynamic AOIs (semi-automatically and manually), measurement of parameters such as dwell times and time to first entry, and overlaying gaze and AOIs on video. Participants (n =11) were asked to look at 13 dynamic AOIs in traffic scenes from appearance to disappearance in order to validate the setup and software. Different AOI margins were explored for the included objects. The median ratio between total appearance time and dwell time was about 90% for most objects when appropriate margins were chosen. This validated open-source toolkit is readily available for researchers who want to perform dynamic AOI analyses with the Pupil Core eye tracker, especially when measurements are desired on a wide screen, in various fields such as psychology, transportation, and low vision research.

Predictive Value of the Esterman Visual Field Test on the Outcome of the On-Road Driving Test.

Purpose: As the prevalence of age-related visual field disorders and the number of older drivers are rising, clear criteria on visual field requirements for driving are important. This article explores the predictive value of the Esterman visual field in relation to the outcome of an on-road driving test. Methods: A retrospective chart review was performed for driver's license applicants who, based on their visual field, performed an on-road driving test. Cases (N = 101) with a failed on-road driving test were matched with 101 controls with a passed outcome. The Esterman visual field was divided in regions, and the number of points missed per region was counted. Logistic regression models and receiver operating characteristic (ROC) curves were computed for each region. Results: Most regions presented a significantly increased odds for failing the driving test when more points were missed. The odds ratio for the whole visual field was 2.52 (95% confidence interval, 1.53-4.14, P < 0.001) for all the participants. However, ROC curves failed to reveal distinct fail-pass criteria based on the number of points missed, as revealed by a large amount of overlap between cases and controls. Conclusions: These findings confirm the relation between visual field damage and impaired driving performance. However, the Esterman visual field results were not conclusive for predicting the driving performance of the individual driver with visual field defects. Translational Relevance: In our group of participants, the number of on-road driving tests cannot be further reduced by a more detailed definition of fail-pass criteria, based on the Esterman visual field test.