Evidence map›Paper›PMID 32737348›Full record

ArticleScientific reports2020

Non-invasive continuous-time glucose monitoring system using a chipless printable sensor based on split ring microwave resonators.

Masoud Baghelani, Zahra Abbasi, Mojgan Daneshmand, Peter E Light

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
8.7field-weighted citation impact, top 1% of its field
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

40 citing papers in PubMed, 191 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Masoud BaghelaniMicrowave to Millimeter Wave (M2M) Lab., Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada. baghelan@ualberta.ca.
Zahra AbbasiMicrowave to Millimeter Wave (M2M) Lab., Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada.
Mojgan DaneshmandMicrowave to Millimeter Wave (M2M) Lab., Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada.
Peter E LightAlberta Diabetes Institute and the Department of Pharmacology, University of Alberta, Edmonton, AB, Canada. plight@ualberta.ca.
University of Alberta · CA

Funding

CIHR
6 · The paper itself

Abstract

This paper reports a highly sensitive, non-invasive sensor for real-time glucose monitoring from interstitial fluid. The structure is comprised of a chip-less tag sensor which may be taped over the patient's skin and a reader, that can be embedded in a smartwatch. The tag sensor is energized through the established electromagnetic coupling between the tag and the reader and its frequency response is reflected on the spectrum of the reader in the same manner. The tag sensor consumes zero power as there is no requirement for any active readout or communication circuitry on the tag side. When measuring changes in glucose concentrations within saline replicating interstitial fluid, the sensor was able to detect glucose with an accuracy of ~ 1 mM/l over a physiological range of glucose concentrations with 38 kHz of the resonance frequency shift. This high sensitivity is attained as a result of the proposed new design and extended field concentration on the tag. The impact of some of the possible interferences on the response of the sensor's performance was also investigated. Variations in electrolyte concentrations within the test samples have a negligible effect on the response of the sensor unless these variations are supra-physiologically large.

Identifiers

PMID32737348
PMCPMC7395170
OpenAlexW3046853010

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.