Evidence map›Paper›PMID 27527174›Full record

ArticleSensors (Basel, Switzerland)2016

Frequency Splitting Analysis and Compensation Method for Inductive Wireless Powering of Implantable Biosensors.

Matthew Schormans, Virgilio Valente, Andreas Demosthenous

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Matthew SchormansDepartment of Electronic and Electrical Engineering, University College London, London WC1E 7JE, UK. matthew.schormans.10@ucl.ac.uk.
Virgilio ValenteDepartment of Electronic and Electrical Engineering, University College London, London WC1E 7JE, UK. v.valente@ucl.ac.uk.
Andreas DemosthenousDepartment of Electronic and Electrical Engineering, University College London, London WC1E 7JE, UK. a.demosthenous@ucl.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inductive powering for implanted medical devices, such as implantable biosensors, is a safe and effective technique that allows power to be delivered to implants wirelessly, avoiding the use of transcutaneous wires or implanted batteries. Wireless powering is very sensitive to a number of link parameters, including coil distance, alignment, shape, and load conditions. The optimum drive frequency of an inductive link varies depending on the coil spacing and load. This paper presents an optimum frequency tracking (OFT) method, in which an inductive power link is driven at a frequency that is maintained at an optimum value to ensure that the link is working at resonance, and the output voltage is maximised. The method is shown to provide significant improvements in maintained secondary voltage and system efficiency for a range of loads when the link is overcoupled. The OFT method does not require the use of variable capacitors or inductors. When tested at frequencies around a nominal frequency of 5 MHz, the OFT method provides up to a twofold efficiency improvement compared to a fixed frequency drive. The system can be readily interfaced with passive implants or implantable biosensors, and lends itself to interfacing with designs such as distributed implanted sensor networks, where each implant is operating at a different frequency.

Indexed as

Biosensing TechniquesElectric Power SuppliesHumansProstheses and ImplantsSoftwareTelemetryWireless Technologyfrequency splittingfrequency tuningimplantable biosensorsinductive linkinductive poweringmedical implantswireless power transfer

Identifiers

PMID27527174
PMCPMC5017394

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.