LAUSR

Objective. How can we return a functional form of sight to people who are living with incurable blindness? Despite recent advances in the development of visual neuroprostheses, the quality of current prosthetic vision is still rudimentary and does not differ much across different device technologies. Approach. Rather than aiming to represent the visual scene as naturally as possible, a Smart Bionic Eye could provide visual augmentations through the means of artificial intelligence-based scene understanding, tailored to specific real-world tasks that are known to affect the quality of life of people who are blind, such as face recognition, outdoor navigation, and self-care. Main results. Complementary to existing research aiming to restore natural vision, we propose a patient-centered approach to incorporate deep learning-based visual augmentations into the next generation of devices. Significance. The ability of a visual prosthesis to support everyday tasks might make the difference between abandoned technology and a widely adopted next-generation neuroprosthetic device.