Diffuse Imaging Approach for Universal Noninvasive Blood Glucose Measurements

Ming Liu, Ge Xu, Yuejin Zhao*, Lingqin Kong*, Liquan Dong, Fen Li*, Mei Hui

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We proposed a diffuse imaging approach for universal noninvasive blood glucose measurements based on visible light, which can predict the blood glucose concentration without personal calibration. The proposed approach used a CCD to obtain diffuse images from human index finger pulp. The denoising autoencoder algorithm adopted effectively extracted the scattering information highly related to blood glucose concentration from the diffuse images, and the gradient boosting regression algorithm enabled an accurate calculation of blood glucose concentration without prior personalized calibration. In vivo experimental results showed that the proposed approach had a mean absolute error of 19.44 mg/dl, with all the predicted results observed within the clinically acceptable region (Region A: 78.9%) in the Clarke error grid analysis. Compared to other blood glucose concentration measurement methods of scattering coefficient, this new method does not require individual calibration, therefore it is easier to implement and popularize, which is critical for the noninvasive monitoring of blood glucose concentration.

Original languageEnglish
Article number853266
JournalFrontiers in Physics
Volume10
DOIs
Publication statusPublished - 25 Mar 2022

Keywords

  • deep feature
  • diffuse image
  • gradient boosting regression
  • noninvasive blood glucose concentration monitoring
  • scattering coefficient

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