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Sze Chuan Ong, Ivy Li Cheng Pek, Carol Tsuey Ling Chiang, Hock Wei Soon, Kuang Chua Chua, Chanakarn Sassman, Victor T C Koh; A novel automated visual acuity test using a portable augmented reality headset.. Invest. Ophthalmol. Vis. Sci. 2019;60(9):5911.
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© ARVO (1962-2015); The Authors (2016-present)
Manual Visual Acuity (VA) testing is an important but relatively time-consuming test required for all patients in the ophthalmology outpatient clinic. It also requires a large number of trained manpower, which could be better deployed elsewhere. The purpose of this study is to develop a reliable automated Augmented Reality (AR) system for VA testing to improve workplace efficiency.
In total, 60 patients from National University Hospital, Singapore were enrolled in a prospective observational study. Each subject underwent VA testing of both eyes with the manual Snellen chart and the AR headset. VA results without pinhole occlusion were analysed with Bland-Altman analysis and intraclass correlation. Other outcome measures included manpower and time, total cost, space needed and patient feedback on ease of use and comfort.
We included 53 out of 60 subjects for the final analysis. There was a clinically insignificant mean difference of 0.05 logMAR (p<0.05), with the AR headset underestimating vision determined by manual testing on the Snellen chart. The 95% limits of agreement were ±0.33 logMAR and intraclass correlation coefficient demonstrated good inter-rater reliability (r=0.77, p<0.05). Automated VA testing increased labour productivity by 157%, reduced direct machinery costs by 67.2% and decreased space consumption by 89.2%. The AR headset was rated mildly uncomfortable but easy to use, with no correlation determined between ease of use and age (r=-0.10, p>0.05) or education levels (r=-0.02, p>0.05).
This study supports the validity of the AR headset as an alternative measurement method of VA to increase workplace efficiency. The AR headset is user-friendly for all, increasing its potential to be used as a community screening tool, and as a platform for other forms of visual testing.
This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.
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