Real-Time Optimization of the Current Steering for Visual Prosthesis

TL;DR

This paper introduces a real-time optimization framework for current steering in neural prostheses, enabling personalized stimulation depth and spatial resolution improvements through efficient electric field computation.

Contribution

It presents a superposition-based linear algebra framework that allows real-time optimization of current steering in neural tissue, overcoming previous computational limitations.

Findings

Real-time optimization of stimulation depth for retinal prostheses.

Enhanced spatial confinement of electric fields for better resolution.

Framework applicable to personalized neural stimulation settings.

Abstract

Current steering on a multi-electrode array is commonly used to shape the electric field in the neural tissue in order to improve selectivity and efficacy of stimulation. Previously, simulations of the electric field in tissue required separate computation for each set of the stimulation parameters. Not only is this approach to modeling time-consuming and very difficult with a large number of electrodes, it is incompatible with real-time optimization of the current steering for practical applications. We present a framework for efficient computation of the electric field in the neural tissue based on superposition of the fields from a pre-calculated basis. Such linear algebraic framework enables optimization of the current steering for any targeted electric field in real time. For applications to retinal prosthetics, we demonstrate how the stimulation depth can be optimized for each patient based on the retinal thickness and separation from the array, while maximizing the lateral confinement of the electric field essential for spatial resolution.