ORCID Profile
0000-0001-7835-3357
Current Organisation
UNSW Sydney
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Publisher: Wiley
Date: 07-02-2023
DOI: 10.1111/OPO.13105
Abstract: S ling and describing the distribution of refractive error in populations is critical to understanding eye care needs, refractive differences between groups and factors affecting refractive development. We investigated the ability of mixture models to describe refractive error distributions. We used key informants to identify raw refractive error datasets and a systematic search strategy to identify published binned datasets of community‐representative refractive error. Mixture models combine various component distributions via weighting to describe an observed distribution. We modelled raw refractive error data with a single‐Gaussian (normal) distribution, mixtures of two to six Gaussian distributions and an additive model of an exponential and Gaussian (ex‐Gaussian) distribution. We tested the relative fitting accuracy of each method via Bayesian Information Criterion (BIC) and then compared the ability of selected models to predict the observed prevalence of refractive error across a range of cut‐points for both the raw and binned refractive data. We obtained large raw refractive error datasets from the United States and Korea. The ability of our models to fit the data improved significantly from a single‐Gaussian to a two‐Gaussian‐component additive model and then remained stable with ≥3‐Gaussian‐component mixture models. Means and standard deviations for BIC relative to 1 for the single‐Gaussian model, where lower is better, were 0.89 ± 0.05, 0.88 ± 0.06, 0.89 ± 0.06, 0.89 ± 0.06 and 0.90 ± 0.06 for two‐, three‐, four‐, five‐ and six‐Gaussian‐component models, respectively, tested across US and Korean raw data grouped by age decade. Means and standard deviations for the difference between observed and model‐based estimates of refractive error prevalence across a range of cut‐points for the raw data were −3.0% ± 6.3, 0.5% ± 1.9, 0.6% ± 1.5 and −1.8% ± 4.0 for one‐, two‐ and three‐Gaussian‐component and ex‐Gaussian models, respectively. Mixture models appear able to describe the population distribution of refractive error accurately, offering significant advantages over commonly quoted simple summary statistics such as mean, standard deviation and prevalence.
Publisher: BMJ
Date: 24-08-2023
Abstract: Baseline ocular surface characteristics in children require investigation. This study characterised blinking and relationships with ocular symptoms, tear film and digital device use. 45 children aged 6–15 years (56% female) participated in a cross-sectional study. Ocular surface symptoms (Instant Ocular Symptoms Survey, Dry Eye Questionnaire 5, Symptoms Assessment in Dry Eye, Ocular Surface Disease Index, Ocular Comfort Index and Numerical Rating Scale) and clinical indices (lipid layer thickness, tear secretion and stability, meibomian gland) were assessed. Blink rate and interblink interval were measured in situ using a wearable eye-tracking headset (Pupil Labs GmbH, Germany). Associations between blinking, ocular surface, age, and digital device use (bivariate and partial correlations) and between automated and manually counted blink rate (Bland & Altman) were examined. Mean blink rate and interblink interval were 20.5±10.5 blinks/min and 2.9±1.9 s during conversation. There was no difference between automated and manual blink rate (p=0.78) and no relationship between blinking and digital device use, age or sex. Mean group symptoms were within normal range and not associated with clinical measurements including blinking. Greater tear volume was associated with a faster blink rate (r=0.46, p=0.001) and shorter interblink interval (r=−0.36, p=0.02). Older age was associated with improved tear volume (r=0.37, p=0.01) and stability (r=0.38, p=0.01). Blinking characterised in situ was not impacted by age or habitual digital device use. A faster blink rate was associated with greater tear volume but not symptoms. Improved tear function was found with age suggesting that the ocular surface continues to develop through childhood.
Publisher: Association for Research in Vision and Ophthalmology (ARVO)
Date: 17-02-2023
DOI: 10.1167/TVST.12.2.28
Publisher: Optica Publishing Group
Date: 11-07-2022
DOI: 10.1364/JOSAA.457663
Abstract: This paper presents and evaluates a system and method that record spatiotemporal scene information and location of the center of visual attention, i.e., spatiotemporal point of regard (PoR) in ecological environments. A primary research application of the proposed system and method is for enhancing current 2D visual attention models. Current eye-tracking approaches collapse a scene’s depth structures to a 2D image, omitting visual cues that trigger important functions of the human visual system (e.g., accommodation and vergence). We combined head-mounted eye-tracking with a miniature time-of-flight camera to produce a system that could be used to estimate the spatiotemporal location of the PoR—the point of highest visual attention—within 3D scene layouts. Maintaining calibration accuracy is a primary challenge for gaze mapping hence, we measured accuracy repeatedly by matching the PoR to fixated targets arranged within a range of working distances in depth. Accuracy was estimated as the deviation from estimated PoR relative to known locations of scene targets. We found that estimates of 3D PoR had an overall accuracy of approximately 2° omnidirectional mean average error (OMAE) with variation over a 1 h recording maintained within 3.6° OMAE. This method can be used to determine accommodation and vergence cues of the human visual system continuously within habitual environments, including everyday applications (e.g., use of hand-held devices).
Publisher: Unpublished
Date: 2019
No related grants have been discovered for Peter Wagner.