Analytical calculation of the self-resonant frequency of biomedical telemetry coils

Zhi Yang, Guoxing Wang, Wentai Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Inductive link is commonly used in biomedical telemetry as a method to wirelessly transmit power and/or data, where coil is very critical to achieve high efficiency. One of the most important but often ignored parameters of the coils is the self-resonant frequency. Due to the fact that the parasitic capacitances are functions of the geometry and winding sequence of the coil, it is very difficult to calculate the self-resonant frequency. The lack of knowledge about the self-resonant frequency greatly limits the design efficiency, especially when the target operating frequency is high, on the order of tens of MHz. This paper presents an analytical model to calculate the self-resonant frequency of multiple-layer coils. A general model of coils to calculate the total parasitic capacitance is given first and then an analytical equation for self-resonant frequency is obtained. The experimental measurement results demonstrate that the equation can accurately predict the self-resonant frequency, therefore can be used for guiding the coil design.

Original languageEnglish
Title of host publication28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Pages5880-5883
Number of pages4
DOIs
Publication statusPublished - 2006
Event28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 - New York, NY, United States
Duration: 2006 Aug 302006 Sept 3

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
ISSN (Print)0589-1019

Other

Other28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Country/TerritoryUnited States
CityNew York, NY
Period06-08-3006-09-03

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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