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A review of biosensor technology and algorithms for glucose monitoring

  • Yaguang Zhang
  • , Jingxue Sun
  • , Liansheng Liu
  • , Hong Qiao*
  • *Corresponding author for this work
  • The Second Affiliated Hospital of Harbin Medical University
  • School of Electronics and Information Engineering, Harbin Institute of Technology

Research output: Contribution to journalReview articlepeer-review

Abstract

Diabetes mellitus (DM) has become a serious illness in the whole world. Until now, there is no effective cure for patients with DM. It is well known that the glucose level is one key factor to determine the progress of DM. It is also an important reference to carry out the accurate and timely treatment for patients with DM. In this article, the related biosensors technology that can be utilized to identify and predict glucose level are reviewed in detail, including the algorithms that can help to achieve numerical value of glucose level. Firstly, the biosensor technology based on the physiological fluids are illustrated, including blood, sweat, interstitial fluid, ocular fluid, and other available fluids. Secondly, the algorithms for achieving numerical value of glucose level are investigated, including the physiological model-based method and the machine learning-based method. Finally, the future development trend and challenges of glucose level monitoring are given and the conclusions are drawn.

Original languageEnglish
Article number107929
JournalJournal of Diabetes and its Complications
Volume35
Issue number8
DOIs
StatePublished - Aug 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Algorithms for glucose analysis
  • Biosensor technology
  • Diabetes mellitus
  • Glucose monitoring

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