December 2019
Volume 19, Issue 15
Open Access
OSA Fall Vision Meeting Abstract  |   December 2019
A virtual reality-based test to assess functional vision in people with simulated ultra low vision
Journal of Vision December 2019, Vol.19, 43. doi:https://doi.org/10.1167/19.15.43
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      Arathy Kartha1, Roksana Sadeghi1,2, Chau Tran3, Zoe Nardo3, Olukemi Adeyemo1, Liancheng Yang1, Duane Geruschat1, Gislin Dagnelie1; A virtual reality-based test to assess functional vision in people with simulated ultra low vision. Journal of Vision 2019;19(15):43. doi: https://doi.org/10.1167/19.15.43.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: Ultra low vision (ULV) is severe visual impairment with visual acuity less than 20/1600. People with ULV have residual vision that enable them to perceive lights and shadows. The purpose of this study was to develop a standardized test to assess functional vision in people with ULV.

Methods: Twenty volunteers wearing translucent patches to simulate ULV participated in this study. Each participant performed a virtual reality based assessment of functional vision that comprised 19 activities developed from a ULV inventory. Each activity had 2, 3 or 4 alternative forced choices and came in three difficulty levels, with 3 trials for each item/level. Responses were scored as 0 for incorrect and 1 for correct.

Results: Responses were analyzed using d prime (d′) analysis. The results showed a wide spread of d′ scores for item measures where the easier task had more negative d' values and vice versa (max = 0.08; min = −3.19; range = 3.27) indicating that the tasks were distributed across a wide range of difficulty levels. Person measures calculated using d' were consistent with the level of simulated visual impairment.

Conclusion: Overall, the current study validated the use of a novel virtual reality based test for assessing functional vision in people with simulated ULV, and its potential use as a robust method to assess functional vision in people with ULV. The portable design allows for easy transport and administration for home based evaluations, which would be an advantage in this population. Further investigation and validation is ongoing in an actual ULV population.

Thank you to all the participants who volunteered for the study. We would like to thank Chris Bradley for his assistance with the statistical analysis and Jack Black and Alfred Vinnett for their assistance with recruitment and testing. 
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