Estimation of blood glucose levels by sweat sensing based on biophysical modeling of glucose transport

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

3 Downloads (Pure)

Abstract

Monitoring glucose concentration in sweat might represent a non-invasive alternative to traditional invasive blood sampling for diabetic patients. The relationship between glucose concentration in blood and in sweat is largely unknown, and methods that can estimate blood glucose levels from measured sweat glucose levels are crucial. In this paper, we present a novel method that was developed by first estimating sweat glucose concentration from blood inputs. Such a method builds on a sweat gland model proposed by La Count et al., additionally considering the dilution effect of different sweat rates between the interstitial space and sweat glands on glucose concentration. The sweat glucose concentration estimated by our model shows an average root mean square percentage error (RMSPE = 11%± 6%), smaller than the original model (RMSPE=21%± 9%). This enables a more accurate estimation of the relationship between glucose levels in sweat and blood. Secondly, solving the inverse problem by an iterative optimization method, we obtained the average RMSPE of blood glucose concentration estimated from the sweat glucose concentration equal to 16.7%± 9.2%. These results show satisfactory prediction accuracy. Our study is the first to realize the estimation of blood glucose changes with high precision based on known sweat glucose concentrations. Furthermore, this research could be significant for the implementation of semi-continuous and prolonged diabetes monitoring by sweat sensing technology.

Original languageEnglish
Title of host publication2023 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2023 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers
Pages1-5
Number of pages5
ISBN (Electronic)978-1-6654-9384-0
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2023 - Jeju, Korea, Republic of
Duration: 14 Jun 202316 Jun 2023

Conference

Conference2023 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2023
Country/TerritoryKorea, Republic of
CityJeju
Period14/06/2316/06/23

Keywords

  • biophysical modeling
  • diabetes
  • glucose monitoring
  • inverse model
  • sweat sensing

Fingerprint

Dive into the research topics of 'Estimation of blood glucose levels by sweat sensing based on biophysical modeling of glucose transport'. Together they form a unique fingerprint.

Cite this