Share Email Print

Proceedings Paper

The discussion about the complexity of samples and the prediction accuracy of glucose concentration in non-invasive blood glucose sensing
Author(s): Xiaoyu Gu; Rong Liu; Wenliang Chen; Kexin Xu
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

A non-invasive and continuous blood glucose monitoring would be of great advantage for diabetic patients. Many techniques have been proposed for the purpose. But so far, none of these methods has been proven to be reliable and precise enough for in vivo monitoring. In non-invasive glucose measurement using near-infrared (NIR) spectroscopy, the difficulty is that the spectral variations due to the glucose concentration are extremely small compared with other sources of variations. Therefore extracting the variation signal of glucose in complicated background is challenging. We investigated the relationship between sample complexity and prediction accuracy, which was the fundamental research of non-invasive sensing and a kind of method to determine whether the OGTT or non-invasive sensing can achieve the required accuracy of clinic. A series of in vitro experiments had been conducted with different complex samples and same measurement system to analyze the relation between the sample complexity and the prediction accuracy, and some conclusions had been drawn. In general, the increase of sample complexity doesn’t lead to the distinct increase of prediction error.

Paper Details

Date Published: 29 March 2005
PDF: 10 pages
Proc. SPIE 5696, Complex Dynamics and Fluctuations in Biomedical Photonics II, (29 March 2005); doi: 10.1117/12.596978
Show Author Affiliations
Xiaoyu Gu, Tianjin Univ. (China)
Rong Liu, Tianjin Univ. (China)
Wenliang Chen, Tianjin Univ. (China)
Kexin Xu, Tianjin Univ. (China)

Published in SPIE Proceedings Vol. 5696:
Complex Dynamics and Fluctuations in Biomedical Photonics II
Valery V. Tuchin, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?