Real-Time Optimization of the Current Steering for Visual Prosthesis

被引:5
|
作者
Chen, Zhijie Charles [1 ,2 ]
Wang, Bing-Yi [2 ,3 ]
Palanker, Daniel [2 ,4 ]
机构
[1] Stanford Univ, Dept Elect Engn, Stanford, CA 94305 USA
[2] Stanford Univ, Hansen Expt Phys Lab, Stanford, CA 94305 USA
[3] Stanford Univ, Dept Phys, Stanford, CA 94305 USA
[4] Stanford Univ, Dept Ophthalmol, Stanford, CA 94305 USA
来源
2021 10TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER) | 2021年
基金
美国国家卫生研究院;
关键词
DEEP BRAIN-STIMULATION;
D O I
10.1109/NER49283.2021.9441400
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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 high spatial resolution.
引用
收藏
页码:592 / 596
页数:5
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