Computer-assisted Adaptive Methods of Measuring Visual Acuity

Computer-assisted Adaptive Methods of Measuring Visual Acuity

Bibliographic Details
Main Author: Andrews, Erin Jessica
Language:English
Published: The Ohio State University / OhioLINK 2017
Subjects:
Optics
Health Sciences
Visual acuity measurement
BestPEST
ZEST
clinical optometry
adaptive computer-assisted visual acuity
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=osu1492549443966615
id ndltd-OhioLink-oai-etd.ohiolink.edu-osu1492549443966615
record_format oai_dc
collection NDLTD
language English
sources NDLTD
topic Optics
Health Sciences
Visual acuity measurement
BestPEST
ZEST
clinical optometry
adaptive computer-assisted visual acuity
spellingShingle Optics
Health Sciences
Visual acuity measurement
BestPEST
ZEST
clinical optometry
adaptive computer-assisted visual acuity
Andrews, Erin Jessica
Computer-assisted Adaptive Methods of Measuring Visual Acuity
author Andrews, Erin Jessica
author_facet Andrews, Erin Jessica
author_sort Andrews, Erin Jessica
title Computer-assisted Adaptive Methods of Measuring Visual Acuity
title_short Computer-assisted Adaptive Methods of Measuring Visual Acuity
title_full Computer-assisted Adaptive Methods of Measuring Visual Acuity
title_fullStr Computer-assisted Adaptive Methods of Measuring Visual Acuity
title_full_unstemmed Computer-assisted Adaptive Methods of Measuring Visual Acuity
title_sort computer-assisted adaptive methods of measuring visual acuity
publisher The Ohio State University / OhioLINK
publishDate 2017
url http://rave.ohiolink.edu/etdc/view?acc_num=osu1492549443966615
work_keys_str_mv AT andrewserinjessica computerassistedadaptivemethodsofmeasuringvisualacuity
_version_ 1719451999583338496
spelling ndltd-OhioLink-oai-etd.ohiolink.edu-osu14925494439666152021-08-03T07:01:44Z Computer-assisted Adaptive Methods of Measuring Visual Acuity Andrews, Erin Jessica Optics Health Sciences Visual acuity measurement BestPEST ZEST clinical optometry adaptive computer-assisted visual acuity Visual acuity measurement has evolved very little throughout the course of its history. Few changes have been proposed and even fewer have been adopted to advance the process of measuring visual ability. One major and widely accepted advancement includes logMAR size progression (Bailey-Lovie and Early Treatment Diabetic Retinopathy Study) chart designs. Logarithmic progression allows for visual acuity measurements to be expanded over a larger range of values, and it also provides the opportunity to quantify acuity changes in terms of “lines of change”. Logarithmic progression also allows for easy letter-by-letter scoring, which is a more accurate and repeatable determination of visual acuity when compared to line-by-line scoring. Additional investigations to improve visual acuity measurement testing have aimed to increase reliability, repeatability, and efficiency. For example, computerized methods of visual acuity testing have been tested. These methods have faced several challenges. Further, adaptive psychophysical methods such as BestPEST and ZEST have been employed in some investigations to improve efficiency and accuracy of threshold visual acuity testing. Adaptive procedures manipulate testing based on previous answers and concentrate testing close to the estimated threshold to efficiently determine an accurate and reliable end point measurement of threshold. Both computer-assisted and adaptive procedures for measuring visual acuity still require investigation and improvement. Visual acuity measurement is one of the most commonly used and most important measures of visual quality and function, and is likely the most commonly used measurement in clinical optometry. Therefore, it is important for the measurement to be standardized and efficient, and its scoring to be accurate, reliable, and repeatable. This study aims to investigate test and scoring procedures in adaptive computer-assisted visual acuity.Computer-assisted VA procedures were evaluated in 52 normally-sighted subjects divided into three experiments. LogMAR procedures were compared to three versions of adaptive methods (PEST, ZEST, and curve fits to the probability of seeing). Repeatability was evaluated as test-retest (TRT) distributions, separated by 1-2 weeks, and by “simultaneous” scores, i.e. trials from test and retest randomly interleaved within the same session. Subjects responded verbally or by typing. LogMAR acuity was measured with a standard logMAR chart, and with a modified single-letter method. Finally, a response-verification procedure required subjects to confirm letter selection in order to minimize typing errors. Test times, mean visual acuity, and test-retest differences were evaluated and compared for all experiments.Within each experiment, the three adaptive scoring methods produced very similar results, with all differences between curve-fitting, PEST and ZEST being less than 0.02 log units, or less than one “letter” of acuity. The method used to run each experiment (CF for Expt 1, ZEST for Expts 2 and 3) also produced the smallest test-retest differences in the final score. Confidence intervals for the between-session conditions were slightly wider than values found in the literature for similar protocols. Within-session TRT values were smaller than between-session values for all experiments, with more than half the variance in between-session repeatability attributed to actual differences in acuity between sessions. The response verification procedure did not produce narrower within-session test-retest distributions compared to other procedures without the required letter confirmation. Within-session repeatability is substantially better than repeatability from sessions separated by days or weeks. Repeatability from sessions separated by days or weeks may be attributed to true visual acuity change over time, whereas repeatability within a session may represent the variability of the testing procedure itself. Adaptive, computer-assisted methods have promise in improving the efficiency and repeatability of VA testing. 2017-09-21 English text The Ohio State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=osu1492549443966615 http://rave.ohiolink.edu/etdc/view?acc_num=osu1492549443966615 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.

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