JOURNAL ARTICLE

Design of the optoelectronic high-resolution retinal prosthesis

Abstract

It has been already demonstrated that electrical stimulation of retina can produce visual percepts in blind patients suffering from macular degeneration and retinitis pigmentosa. Current retinal implants provide very low resolution (just a few electrodes), while several thousand pixels are required for functional restoration of sight. We present a design of the optoelectronic retinal prosthetic system that can activate a retinal stimulating array with pixel density up to 2,500 pix/mm2 (geometrically corresponding to a visual acuity of 20/80), and allows for natural eye scanning rather than scanning with a head-mounted camera. The system operates similarly to "virtual reality" imaging devices used in military and medical applications. An image from a video camera is projected by a goggle-mounted infrared LED-LCD display onto the retina, activating an array of powered photodiodes in the retinal implant. Such a system provides a broad field of vision by allowing for natural eye scanning. The goggles are transparent to visible light, thus allowing for simultaneous utilization of remaining natural vision along with prosthetic stimulation. Optical control of the implant allows for simple adjustment of image processing algorithms and for learning. A major prerequisite for high resolution stimulation is the proximity of neural cells to the stimulation sites. This can be achieved with sub-retinal implants constructed in a manner that directs migration of retinal cells to target areas. Two basic implant geometries are described: perforated membranes and protruding electrode arrays. Possibility of the tactile neural stimulation is also examined.

Keywords:
Retinal implant Visual prosthesis Retina Computer science Image sensor Photodiode Materials science Electrode array Retinal Computer vision Optics Retinitis pigmentosa Biomedical engineering Artificial intelligence Optoelectronics Electrode Medicine Physics Ophthalmology

Metrics

6
Cited By
0.12
FWCI (Field Weighted Citation Impact)
24
Refs
0.40
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Neuroscience and Neural Engineering
Life Sciences →  Neuroscience →  Cellular and Molecular Neuroscience
Advanced Memory and Neural Computing
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
EEG and Brain-Computer Interfaces
Life Sciences →  Neuroscience →  Cognitive Neuroscience

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