Evidence mapPaperPMID 35062385Full record

ReviewSensors (Basel, Switzerland)2022

Commercial and Scientific Solutions for Blood Glucose Monitoring-A Review.

Yirui Xue, Angelika S Thalmayer, Samuel Zeising, Georg Fischer, Maximilian Lübke

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Blood glucose estimation based on ECG signal.Physical and engineering sciences in medicine · 2023
    Article
  13. Article
  14. Article
  15. Review
  16. Review
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

5 authors.

Yirui XueInstitute for Electronics Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstr. 9, 91058 Erlangen, Germany.ORCID 0000-0002-3841-8264
Angelika S ThalmayerInstitute for Electronics Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstr. 9, 91058 Erlangen, Germany.ORCID 0000-0001-6681-5497
Samuel ZeisingInstitute for Electronics Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstr. 9, 91058 Erlangen, Germany.ORCID 0000-0001-9187-1386
Georg FischerInstitute for Electronics Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstr. 9, 91058 Erlangen, Germany.ORCID 0000-0002-4033-2005
Maximilian LübkeInstitute for Electronics Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstr. 9, 91058 Erlangen, Germany.ORCID 0000-0001-6527-8925

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes is a chronic and, according to the state of the art, an incurable disease. Therefore, to treat diabetes, regular blood glucose monitoring is crucial since it is mandatory to mitigate the risk and incidence of hyperglycemia and hypoglycemia. Nowadays, it is common to use blood glucose meters or continuous glucose monitoring via stinging the skin, which is classified as invasive monitoring. In recent decades, non-invasive monitoring has been regarded as a dominant research field. In this paper, electrochemical and electromagnetic non-invasive blood glucose monitoring approaches will be discussed. Thereby, scientific sensor systems are compared to commercial devices by validating the sensor principle and investigating their performance utilizing the Clarke error grid. Additionally, the opportunities to enhance the overall accuracy and stability of non-invasive glucose sensing and even predict blood glucose development to avoid hyperglycemia and hypoglycemia using post-processing and sensor fusion are presented. Overall, the scientific approaches show a comparable accuracy in the Clarke error grid to that of the commercial ones. However, they are in different stages of development and, therefore, need improvement regarding parameter optimization, temperature dependency, or testing with blood under real conditions. Moreover, the size of scientific sensing solutions must be further reduced for a wearable monitoring system.

Indexed as

Diabetes MellitusHypoglycemiaBlood GlucoseBlood Glucose Self-MonitoringHumansMonitoring, PhysiologicReproducibility of ResultsBlood Glucoseblood glucose monitoringClarke error gridcommercialdiabetes mellitusmachine learningmicrowavenon-invasive monitoringreview

Identifiers

PMID35062385
PMCPMC8780031

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.