A Comprehensive Comparative Study on Inductive and Ultrasonic Wireless Power Transmission to Biomedical Implants

Ahmed Ibrahim, Miao Meng, Mehdi Kiani

Research output: Contribution to journalArticlepeer-review

51 Scopus citations


This paper presents a comprehensive comparison between inductive coupling and ultrasound for wireless power transmission to biomedical implants. Several sets of inductive and ultrasonic links for different powering distances (d12) and receiver dimensions have been optimized, and their key parameters, including power transmission efficiency (PTE) and power delivered to the load (PDL) within safety constraints, have been compared to find out which method is optimal for any given condition. Two design procedures have been presented for maximizing the PTE of inductive and ultrasonic links by finding the optimal geometry for the transmitter and receiver (Rx) coils and ultrasonic transducers as well as the optimal operation frequency (fp). Our simulation and measurement results showed that the ultrasonic link transcends the inductive link in PTE and somewhat in PDL for a small Rx of 1.1 mm3 (diameter of 1.2 mm), particularly when the Rx was deeply implanted inside the tissue (d12≥ 10mm). However, for a larger 20 mm3 Rx (diameter of 5 mm), the inductive link achieved higher PTE and PDL, particularly at shorter distances (d12 < 30 mm). The optimal loading condition is shown to be quite different in inductive and ultrasonic links. Despite higher performance for small Rx and large d12 , the ultrasonic link is more sensitive to Rx misalignments and orientations. This led us to propose a new design procedure based on the worst-case misalignment scenario. The simulation results have been validated by measurements. The inductive and ultrasonic links, operating at 30 and 1.1 MHz, achieved measured PTEs of 0.05% and 0.65% for the 1.1 mm3 Rx located 30 mm inside tissue and oil environments with optimal load resistances of 295Ω and 3.8 kΩ, respectively.

Original languageEnglish (US)
Pages (from-to)3813-3826
Number of pages14
JournalIEEE Sensors Journal
Issue number9
StatePublished - May 1 2018

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Electrical and Electronic Engineering


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