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Modeling and Characterization of Capacitive Elements With Tissue as Dielectric Material for Wireless Powering of Neural Implants

This paper reports on the modeling and characterization of capacitive elements with tissue as the dielectric material, representing the core building block of a capacitive link for wireless power transfer to neural implants. Each capacitive element consists of two parallel plates that are aligned ar...

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Bibliographic Details
Published in:IEEE transactions on neural systems and rehabilitation engineering 2018-05, Vol.26 (5), p.1093-1099
Main Authors: Erfani, Reza, Marefat, Fatemeh, Sodagar, Amir M., Mohseni, Pedram
Format: Article
Language:English
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Summary:This paper reports on the modeling and characterization of capacitive elements with tissue as the dielectric material, representing the core building block of a capacitive link for wireless power transfer to neural implants. Each capacitive element consists of two parallel plates that are aligned around the tissue layer and incorporate a grounded, guarded, capacitive pad to mitigate the adverse effect of stray capacitances and shield the plates from external interfering electric fields. The plates are also coated with a biocompatible, insulating, coating layer on the inner side of each plate in contact with the tissue. A comprehensive circuit model is presented that accounts for the effect of the coating layers and is validated by measurements of the equivalent capacitance as well as impedance magnitude/phase of the parallel plates over a wide frequency range of 1 kHz-10 MHz. Using insulating coating layers of Parylene-C at a thickness of 7.5 μm and Parylene-N at a thickness of 1 μm deposited on two sets of parallel plates with different sizes and shapes of the guarded pad, our modeling and characterization results accurately capture the effect of the thickness and electrical properties of the coating layers on the behavior of the capacitive elements over frequency and with different tissues.
ISSN:1534-4320
1558-0210
DOI:10.1109/TNSRE.2018.2824281