Performance of Complex Visual Tasks using Simulated Prosthetic Vision via Augmented-Reality Glasses
PurposePhotovoltaic 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.\n\nMethodsAR glasses with blocked central 20{degrees} 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.\n\nResultsWith 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{degrees}). In the face recognition task (4-way forced choice, 5{degrees} angular size) participants identified faces at >75% accuracy, even with 100 m pixels and only 2 grey levels. With 60 m pixels and 8 grey levels, the accuracy exceeded 97%.\n\nConclusionsSubjects 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 m/pixel resolution. These results indicate feasibility of the reading and face recognition using prosthetic central vision even with 100 m pixels, and performance improves further with smaller pixels.