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A mixed integer linear programming framework for improving cortical vision prosthesis designs
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AI
DOI：10.1016/j.bspc.2022.104253.png)
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Abstract
En 中文
Although cortical vision prosthesis design has been an active area of research since the early 70s, progress in performance remains quite limited. This paper aims to develop a rigorous mathematical framework, based on mixed integer programming, for the analysis of the cortical vision prosthesis design problem and the optimal estimation of a prosthesis setup parameters. The simulated examples illustrate the unique capabilities of the proposed strategy in testing the feasibility of the goals of a prosthesis under a set of specified design constraints. Investigation of the results of the simulated examples suggest that a number of electrodes much larger than the number of cortical locations that are to be controlled is needed to achieve an improved vision experience, approaching the quality of normal vision (to reach a 300 pixels/inch resolution a million-electrode implantation is required). Thus, future research should focus on how these electrodes can be safely implanted. Once this is possible, the proposed framework can be applied to decide their optimal locations and excitation currents.
Keywords:
Electrical brain stimulation
Cortical vision prosthesis
Mixed integer linear programming (MILP)
Optimization
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4.9
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