Machine Learning Approach for Non-Invasive Detection of Blood Glucose Concentration using Microwave

Y. N.R. Reddy, K. T. Chandrasekaran, M. F. Karim, A. Alphones, M. Y. Siyal, A. Q. Liu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

A non-invasive blood glucose measurement method based on microwave transmission and applying machine learning technique to the data obtained, is proposed for monitoring the patients' blood glucose level. Using this technique, non-invasive measurement of the blood glucose concentration at the earlobe portion can be realized and put into use by analysing the reflected microwave signals. A third order Cole-Cole equation is derived to model the dielectric properties of human tissues. Particle swarm optimisation technique is used to determine the coefficients for the glucose concentration dependent equations. With these estimated dielectric values of human tissues, human earlobe portion is modelled and tested at a wide range of frequencies to analyse for the region of linearity. It was observed that frequency range from 6-8 GHz shows the linearity and calculating the complex permittivity values with the help of transmission parameters. Applying Machine-learning technique to the above process can facilitate a real-time processing which in turn is able to alert patients during hyperglycemia conditions, and can suggest a precise dose of insulin to intake.

Original languageEnglish
Title of host publicationProceedings on 2018 International Conference on Advances in Computing and Communication Engineering, ICACCE 2018
EditorsVishal Kumar, S. D. Sudarsan, Ravi Tomar
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages89-91
Number of pages3
ISBN (Print)9781538644850
DOIs
Publication statusPublished - 20 Aug 2018
Externally publishedYes
Event2018 International Conference on Advances in Computing and Communication Engineering, ICACCE 2018 - Paris, France
Duration: 22 Jun 201823 Jun 2018

Publication series

NameProceedings on 2018 International Conference on Advances in Computing and Communication Engineering, ICACCE 2018

Conference

Conference2018 International Conference on Advances in Computing and Communication Engineering, ICACCE 2018
Country/TerritoryFrance
CityParis
Period22/06/1823/06/18

Keywords

  • Blood Glucose
  • Cole-cole model
  • diabetes
  • hyperglycemia
  • machine learning
  • microwave
  • particle swarm optimisation

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computer Networks and Communications
  • Hardware and Architecture

Fingerprint

Dive into the research topics of 'Machine Learning Approach for Non-Invasive Detection of Blood Glucose Concentration using Microwave'. Together they form a unique fingerprint.

Cite this