Evidence map›Paper›PMID 35684748›Full record

ArticleSensors (Basel, Switzerland)2022

A Contactless Glucose Solution Concentration Measurement System Based on Improved High Accurate FMCW Radar Algorithm.

Chengjie Liu, Yuan Du, Li Du

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 26% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 1 institution in 1 country.

Chengjie LiuSchool of Electronic Science and Engineering, Nanjing University, Nanjing 210000, China.ORCID 0000-0002-0217-7008
Yuan DuSchool of Electronic Science and Engineering, Nanjing University, Nanjing 210000, China.ORCID 0000-0002-5316-619X
Li DuSchool of Electronic Science and Engineering, Nanjing University, Nanjing 210000, China.
Nanjing University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To reduce the pain and the probability of cross-infection caused by the invasive blood glucose testing instruments, the ex vivo glucose measurement is of high significance. The electrical property of blood varies with the density of the glucose, which can be sensed by measuring its reflected coefficient in millimeter-wave. In this article, we built a contactless glucose solution concentration measurement system based on 77-GHz FMCW radar. Several preliminary signal processing algorithms are cascaded with a deep neural network to improve the accuracy of glucose solution concentration measurement. Our experiment shows that the resolution of this ex vivo glucose measurement can achieve up to 0.1 mg/mL.

Indexed as

RadarSignal Processing, Computer-AssistedAlgorithmsGlucoseGlucoseconvolutional neural networkdeep learning algorithmFMCW radarPSDsparrow search algorithmwavelet transform

Identifiers

PMID35684748
PMCPMC9185531
OpenAlexW4281759306

What OpenQuestion 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 OpenQuestion graph.