Enhanced Artificial Vision for Visually Impaired Using Visual Implants

Abstract

Argus II is the most advanced retina implants approved by the US FDA and almost 350 visually impaired people are using it. This implant uses 60 microelectrodes implanted in the retina. The goal of this implant is to improve mobility and quality of life of its users. However, users’ satisfaction is not very high due to the very low resolution of the phosphene images and features created by this device. This article proposes a system to improve the artificial vision created by visual implants. The proposed method extracts information about the people around the visually impaired person by using image processing and machine vision algorithms. This information includes the number of the people in the scene, whether they are known or unknown, their gender, estimated ages, facial emotions, and approximate distance from the visually impaired person. This information is extracted from the frames received by a camera mounted on the glasses of the user to generate signals that are fed into a visual stimulator. This information is shown to the user by a schematic vision created by some pre-trained patterns of phosphenes reflecting the information communicated to the user. The proposed system is validated with a simulated prosthetic vision comprising 150 microelectrodes that is compatible with the retina and visual cortex implants. A low-cost and energy efficient implementation of the proposed method executing on a Raspberry Pi 4 B at a frame rate of 4.5 frames/second shows the feasibility of using it in portable systems.

Keywords

• Argus II
• artificial vision for visually impaired people
• simulated prosthetic vision
• scene understanding
• visual prosthesis
• visual implants