Blood glucose prediction using neural network

被引：2

作者：

Soh, Chit Siang ^{[1
]}

Zhang, Xiqin ^{[2
]}

Chen, Jianhong

Raveendran, P. ^{[1
,3
]}

Soh, Phey Hong

Yeo, Joon Hock

机构：

[1] Univ Malaya, Kuala Lumpur, Malaysia

[2] Glucostats Syst, Singapore, Singapore

[3] Univ Malaya, Kuala Lumpur, Malaysia

来源：

ADVANCED BIOMEDICAL AND CLINICAL DIAGNOSTIC SYSTEMS VI | 2008年 / 6848卷

关键词：

neural network; blood glucose; non-invasive measurement;

D O I：

10.1117/12.762529

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

We used neural network for blood glucose level determination in this study. The data set used in this study was collected using a non-invasive blood glucose monitoring system with six laser diodes, each laser diode operating at distinct near infrared wavelength between 1500nm and 1800nm. The neural network is specifically used to determine blood glucose level of one individual who participated in an oral glucose tolerance test (OGTT) session. Partial least squares regression is also used for blood glucose level determination for the purpose of comparison with the neural network model. The neural network model performs better in the prediction of blood glucose level as compared with the partial least squares model.

引用

页数：5

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