A Low-cost and Enzyme-free Glucose Paper Sensor

Zheyuan Chen, Ting Yen Chi, Onder Dincel, Lin Tong, Jun Kameoka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A low-cost and enzyme-free glucose paper sensor is presented as a promising alternative to glucose test strips. This paper-based glucose sensor is prepared with molecularly imprinted (MIP) polyaniline (PANI) electrode. The determination of glucose concentrations was studied by the impedance change of the paper sensor before and after the blood samples dispensing at a low frequency. A comparison of the linear and polynomial regression was applied to analyze the impedance ratio as a function of glucose concentrations. The proposed glucose paper sensor showed a limit of detection (LoD) of 1.135 mM. This novel and non-enzymatic paper sensor suggests a low-cost glucose test assay and can improve the quality of routine testing for diabetic patients.

Original languageEnglish
Title of host publication42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEnabling Innovative Technologies for Global Healthcare, EMBC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4097-4100
Number of pages4
ISBN (Electronic)9781728119908
DOIs
Publication statusPublished - 2020 Jul
Externally publishedYes
Event42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada
Duration: 2020 Jul 202020 Jul 24

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2020-July
ISSN (Print)1557-170X

Conference

Conference42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
Country/TerritoryCanada
CityMontreal
Period20/7/2020/7/24

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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