Safe inductive power transmission to millimeter-sized implantable microelectronics devices

Ahmed Ibrahim, Mehdi Kiani

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

11 Scopus citations

Abstract

Power transfer efficiency (PTE) and power delivered to the load (PDL) are key inductive link design parameters for powering millimeter-sized implants. While several groups have suggested increasing the power carrier frequency (∞p) of inductive links to 100s of MHz to maximize PTE, we have demonstrated that operating at 10s of MHz offers higher allowable PDL under the safety absorption rate (SAR) constraints. We have proposed a closed-form power function that relates maximum power levels that can safely be transferred at different frequencies under the SAR constraints. Three sets of inductive links at different frequencies of 50 MHz, 200 MHz, and 400 MHz have been optimized for powering a 1 mm3-sized implant. We have shown in simulations that reducing ∞p from 200 MHz to 50 MHz along with shrinking the size of the transmitter coil results in ∼7.8 times higher PDL under SAR constraints, at the cost of only 52% drop in PTE.

Original languageEnglish (US)
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages817-820
Number of pages4
ISBN (Electronic)9781424492718
DOIs
StatePublished - Nov 4 2015
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: Aug 25 2015Aug 29 2015

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Country/TerritoryItaly
CityMilan
Period8/25/158/29/15

All Science Journal Classification (ASJC) codes

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

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