Clinical Progress and Optimization of Information Processing in Artificial Visual Prostheses

Abstract

Visual prostheses, used to assist in restoring functional vision to the visually impaired, convert captured external images into corresponding electrical stimulation patterns that are stimulated by implanted microelectrodes to induce phosphenes and eventually visual perception. Detecting and providing useful visual information to the prosthesis wearer under limited artificial vision has been an important concern in the field of visual prosthesis. Along with the development of prosthetic device design and stimulus encoding methods, researchers have explored the possibility of the application of computer vision by simulating visual perception under prosthetic vision. Effective image processing in computer vision is performed to optimize artificial visual information and improve the ability to restore various important visual functions in implant recipients, allowing them to better achieve their daily demands. This paper first reviews the recent clinical implantation of different types of visual prostheses, summarizes the artificial visual perception of implant recipients, and especially focuses on its irregularities, such as dropout and distorted phosphenes. Then, the important aspects of computer vision in the optimization of visual information processing are reviewed, and the possibilities and shortcomings of these solutions are discussed. Ultimately, the development direction and emphasis issues for improving the performance of visual prosthesis devices are summarized.

Gaze-contingent processing improves mobility, scene recognition and visual search in simulated head-steered prosthetic vision

“…Even given the rapid recent developments (for instance, see [7,8]) it is clear that the quality of the prosthetic vision will be relatively elementary compared to natural vision. This forms the motivation for an active line of research studying the expected functionality and utility in relation to specific design choices in the development [9,10].…”

A computational model to design wide field-of-view optic nerve neuroprostheses

“…Specifically, semantic segmentation allows us to identify individual salient objects inside a complex scene and to customize the stimulation based on the context surrounding the user, and their needs. [30]. Here, we use a set of RGB images with an additional channel for encoding depth information (RGB-D images captured in different settings (seated at a table, indoor, outdoor).…”

Electrophysiological properties of layer 2/3 pyramidal neurons in the primary visual cortex of a retinitis pigmentosa mouse model (rd10)

“…Several therapeutic approaches, such as optogenetic, pharmacological, or electrical stimulation, were used in animal models of retinitis pigmentosa to elicit activity in retinal and downstream circuits to restore vision or delay retinal degeneration (Aghaizu et al, 2017 ; Dias et al, 2018 ; Ayton et al, 2020 ; Farnum and Pelled, 2020 ; Kleinlogel et al, 2020 ; Prosseda et al, 2022 ). In human patients, electrical stimulation of retinal ganglion cells via retinal implants is able to elicit reliable responses in the visual cortex of RP patients, but the perception is usually restricted to light flashes or phosphenes (Humayun et al, 2012 ; Keserü et al, 2012 ; Yue et al, 2021 ; Wang et al, 2022 ). One reason for the limited success of these approaches, in addition to retinal changes, might be found in an altered visual system that has already undergone homeostatic changes due to the lack of visual input (Bhattacharyya, 2022 ; Caravaca-Rodriguez et al, 2022 ).…”