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• W2314003670 abstract "Electronic biomedical implantable sensors need power to perform. Among the main reported approaches, inductive link is the most commonly used method for remote powering of such devices. Power efficiency is the most important characteristic to be considered when designing inductive links to transfer energy to implantable biomedical sensors. The maximum power efficiency is obtained for maximum coupling and quality factors of the coils and is generally limited as the coupling between the inductors is usually very small. This paper is dealing with geometry optimization of inductively coupled printed spiral coils for powering a given implantable sensor system. For this aim, Iterative Procedure (IP) and Genetic Algorithm (GA) analytic based optimization approaches are proposed. Both of these approaches implement simple mathematical models that approximate the coil parameters and the link efficiency values. Using numerical simulations based on Finite Element Method (FEM) and with experimental validation, the proposed analytic approaches are shown to have improved accurate performance results in comparison with the obtained performance of a reference design case. The analytical GA and IP optimization methods are also compared to a purely Finite Element Method based on numerical optimization approach (GA-FEM). Numerical and experimental validations confirmed the accuracy and the effectiveness of the analytical optimization approaches to design the optimal coil geometries for the best values of efficiency." @default.
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• W2314003670 date "2016-01-01" @default.
• W2314003670 modified "2023-10-16" @default.
• W2314003670 title "Geometry Optimization Approaches of Inductively Coupled Printed Spiral Coils for Remote Powering of Implantable Biomedical Sensors" @default.
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• W2314003670 doi "https://doi.org/10.1155/2016/4869571" @default.
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