Evidence map›Paper›PMID 38495721›Full record

ArticleBiomedical optics express2024

High-precision sensor for glucose solution using active multidimensional feature THz spectroscopy.

Min Zhang, Jiarui Liu, Nan Wang, Bingyuan Zhang, Feilong Gao, Minghong Wang, Qi Song

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomedical optics express, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

7 authors.

Min ZhangShenzhen Key Laboratory of Laser Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, The State Key Laboratory of Transient Optics and Photonics, Shenzhen University, Shenzhen 518060, China.
Jiarui LiuShenzhen Key Laboratory of Laser Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, The State Key Laboratory of Transient Optics and Photonics, Shenzhen University, Shenzhen 518060, China.ORCID https://orcid.org/0009-0006-5082-7083
Nan WangShenzhen Key Laboratory of Laser Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, The State Key Laboratory of Transient Optics and Photonics, Shenzhen University, Shenzhen 518060, China.
Bingyuan ZhangShandong Key Laboratory of Optical Communication Science and Technology, School of Physics Science and Information Technology, Liaocheng University, Liaocheng, 252059, China.
Feilong GaoShandong Key Laboratory of Optical Communication Science and Technology, School of Physics Science and Information Technology, Liaocheng University, Liaocheng, 252059, China.
Minghong WangShandong Key Laboratory of Optical Communication Science and Technology, School of Physics Science and Information Technology, Liaocheng University, Liaocheng, 252059, China.
Qi SongShenzhen Key Laboratory of Laser Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, The State Key Laboratory of Transient Optics and Photonics, Shenzhen University, Shenzhen 518060, China.ORCID https://orcid.org/0000-0002-1167-871X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Terahertz waves are known for their bio-safety and spectral fingerprinting features, and terahertz spectroscopy technology holds great potential for both qualitative and quantitative identification in the biomedical field. There has been a substantial amount of research utilizing this technology in conjunction with machine learning algorithms for substance identification. However, due to the strong absorption of water for terahertz waves, the single-dimensional features of the sample become indistinct, thereby diminishing the efficiency of the algorithmic recognition. Building upon this, we propose a method that employs terahertz time-domain spectroscopy (THz-TDS) in conjunction with multidimensional feature spectrum identification for the detection of blood sugar and glucose mixtures. Our research indicates that combining THz-TDS with multidimensional feature spectrum and linear discriminant analysis (LDA) algorithms can effectively identify glucose concentrations and detect adulteration. By integrating the multidimensional feature spectrum, the identification success rate increased from 68.9% to 96.0%. This method offers an economical, rapid, and safe alternative to traditional methods and can be applied in blood sugar monitoring, sweetness assessment, and food safety.

Identifiers

PMID38495721
PMCPMC10942695

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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.