pulse2percept: A Python-based simulation framework for bionic vision
Michael Beyeler
Geoffrey M. Boynton
Ione Fine
Ariel Rokem
Video: https://youtu.be/KxsNAa-P2X4
Abstract
By 2020 roughly 200 million people worldwide will suffer from photoreceptor
diseases such as retinitis pigmentosa and age-related macular degeneration,
and a variety of retinal sight restoration technologies are being developed
to target these diseases. One technology, analogous to cochlear implants, uses a grid of electrodes to
stimulate remaining retinal cells.
Two brands of retinal prostheses are currently approved for implantation in patients
with late stage photoreceptor disease.
Clinical experience with these implants has made it apparent that
the vision restored by these devices differs substantially
from normal sight. To better understand the outcomes of this technology,
we developed pulse2percept, an open-source Python implementation
of a computational model that predicts the perceptual experience
of retinal prosthesis patients across a wide range of implant configurations.
A modular and extensible user interface
exposes the different building blocks of the software,
making it easy for users to simulate
novel implants, stimuli, and retinal models.
We hope that this library will contribute substantially to the field of medicine
by providing a tool to accelerate the development of visual prostheses.
bionic vision, retinal implant, pulse2percept, prosthesis
DOI10.25080/shinma-7f4c6e7-00c