Background: The growing global burden of visual impairment necessitates better population eye screening for early detection of eye diseases. However, accessibility to testing is often limited and centralized at in-hospital settings. Furthermore, many eye screening programs were disrupted by the COVID-19 pandemic, presenting an urgent need for out-of-hospital solutions.
Objective: This study investigates the performance of a novel remote perimetry application designed in a virtual reality metaverse environment to enable functional testing in community-based and primary care settings.
Methods: This was a prospective observational study investigating the performance of a novel remote perimetry solution in comparison with the gold standard Humphrey visual field (HVF) perimeter. Subjects received a comprehensive ophthalmologic assessment, HVF perimetry, and remote perimetry testing. The primary outcome measure was the agreement in the classification of overall perimetry result normality by the HVF (Swedish interactive threshold algorithm-fast) and testing with the novel algorithm. Secondary outcome measures included concordance of individual testing points and perimetry topographic maps.
Results: We recruited 10 subjects with an average age of 59.6 (range 28-81) years. Of these, 7 (70%) were male and 3 (30%) were female. The agreement in the classification of overall perimetry results was high (9/10, 90%). The pointwise concordance in the automated classification of individual test points was 83.3% (8.2%; range 75%-100%). In addition, there was good perimetry topographic concordance with the HVF in all subjects.
Conclusions: Remote perimetry in a metaverse environment had good concordance with gold standard perimetry using the HVF and could potentially avail functional eye screening in out-of-hospital settings.
Keywords: HVF; digital health; eye; functional testing; glaucoma; metaverse; ophthalmologic; ophthalmology; perimetry test; remote care; screening; virtual reality; visual field; visual impairment; visually impaired.
©Kang-An Wong, Bryan Chin Hou Ang, Dinesh Visva Gunasekeran, Rahat Husain, Joewee Boon, Krishna Vikneson, Zyna Pei Qi Tan, Gavin Siew Wei Tan, Tien Yin Wong, Rupesh Agrawal. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 19.10.2023.