Performance of Complex Visual Tasks using Simulated Prosthetic Vision via Augmented-Reality Glasses
Purpose: Photovoltaic subretinal prosthesis is designed for restoration of central vision in patients with age-related macular degeneration (AMD). We investigated the utility of prosthetic central vision for complex visual tasks using augmented-reality (AR) glasses simulating reduced acuity, contras...
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Published in | bioRxiv |
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Main Authors | , , |
Format | Paper |
Language | English |
Published |
Cold Spring Harbor
Cold Spring Harbor Laboratory Press
22.07.2019
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Subjects | |
Online Access | Get full text |
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Summary: | Purpose: Photovoltaic subretinal prosthesis is designed for restoration of central vision in patients with age-related macular degeneration (AMD). We investigated the utility of prosthetic central vision for complex visual tasks using augmented-reality (AR) glasses simulating reduced acuity, contrast and visual field. Methods: AR glasses with blocked central 20° of visual field included an integrated video camera and software which adjusts the image quality according to three user-defined parameters: resolution, corresponding to the equivalent pixel size of an implant, field of view, corresponding to the implant size, and number of contrast levels. The real-time processed video was streamed on a screen in front of the right eye. Nineteen healthy participants were recruited to complete visual tasks including vision charts, sentence reading, and face recognition. Results: With vision charts, letter acuity exceeded the pixel-sampling limit by 0.2 logMAR. Reading speed decreased with increasing pixel size and with reduced field of view (7-12°). In the face recognition task (4-way forced choice, 5° angular size) participants identified faces at >75% accuracy, even with 100 μm pixels and only 2 grey levels. With 60 μm pixels and 8 grey levels, the accuracy exceeded 97%. Conclusions: Subjects with simulated prosthetic vision performed slightly better than the sampling limit on the letter acuity tasks, and were highly accurate at recognizing faces, even with 100 μm/pixel resolution. These results indicate feasibility of the reading and face recognition using prosthetic central vision even with 100 μm pixels, and performance improves further with smaller pixels. |
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DOI: | 10.1101/707851 |