Review of Non-Invasive Blood Glucose Level Estimation based on Photoplethysmography and Artificial Intelligent Technology

Ernia Susana, Kalamullah Ramli

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The emergence of photoplethysmography for the non-invasive estimation of blood glucose levels in diabetes management offers an alternative solution to the limitations of invasive methods. The application of artificial intelligence technology to PPG signals for non-invasive measurement of monitoring blood glucose level (BGL) using either a machine learning (ML) or deep learning (DL) approach is proven to improve the resulting performance. This review is presented to provide concise information about current and proposed technologies developments of non-invasive blood glucose level monitoring methods using photoplethysmography. The study focuses on the opportunities and constraints in developing research on this topic.

Original languageEnglish
Title of host publication17th International Conference on Quality in Research, QIR 2021
Subtitle of host publicationInternational Symposium on Electrical and Computer Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages158-163
Number of pages6
ISBN (Electronic)9781665496964
DOIs
Publication statusPublished - 2021
Event17th International Conference on Quality in Research, QIR 2021: International Symposium on Electrical and Computer Engineering - Virtual, Online, Indonesia
Duration: 13 Oct 202115 Oct 2021

Publication series

Name17th International Conference on Quality in Research, QIR 2021: International Symposium on Electrical and Computer Engineering

Conference

Conference17th International Conference on Quality in Research, QIR 2021: International Symposium on Electrical and Computer Engineering
Country/TerritoryIndonesia
CityVirtual, Online
Period13/10/2115/10/21

Keywords

  • artificially intelligence
  • blood glucose level
  • deep learning
  • estimation
  • machine learning
  • non-invasive
  • photoplethysmography
  • PPG signal

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