AI-Powered Artificial Vision for Visual Prostheses

Visual impairment is one of the ten most prevalent causes of disability and poses extraordinary challenges to individuals in our society that relies heavily on sight. Living with acquired blindness not only lowers the quality of life of these individuals, but also strains society's limited resources for assistance, care and rehabilitation. However, to date, there is no effective treatment for man patients who are visually handicapped as a result of degeneration or damage to the inner layers of the retina, the optic nerve or the visual pathways. Therefore, there are compelling reasons to pursue the development of a cortical visual prosthesis capable of restoring some useful sight in these profoundly blind patients. However, the quality of current prosthetic vision is still rudimentary. A major outstanding challenge is translating electrode stimulation into a code that the brain can understand. Interactions between the device electronics and the retinal neurophysiology lead to distortions that can severely limit the quality of the generated visual experience. Rather than aiming to one day restore natural vision (which may remain elusive until the neural code of vision is fully understood), one might be better off thinking about how to create practical and useful artificial vision now. The goal of this work is to address fundamental questions that will allow the development of a Smart Bionic Eye, a device that relies on AI-powered scene understanding to augment the visual scene (similar to the Microsoft HoloLens), tailored to specific real-world tasks that are known to diminish the quality of life of people who are blind (e.g., face recognition, outdoor navigation, reading, self-care).

NCT Number	NCT06117332
Lead Sponsor	University of California, Santa Barbara Collaborators: Universidad Miguel Hernandez de Elche
Conditions	Blindness, Acquired
Enrollment	7 participants
Start Date	2023-10-02
Primary Completion	2027-08-31 (estimated)
Study Completion	2027-08-31 (estimated)
Updated on ClinicalTrials.gov	2025-07-31