Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/6587
Title: Improved stability of blood glucose measurement in humans using near infrared spectroscopy
Authors: So, CF
Chung, J
Siu, SMM
Wong, TKS
Keywords: Blood glucose
Partial least squares
Near infrared
Prediction model
Spectroscopy
Issue Date: 2011
Publisher: Hindawi Publishing Corporation
Source: Spectroscopy, 2011, v. 25, no. 3-4, p. 137-145 How to cite?
Journal: Spectroscopy 
Abstract: Near infrared (NIR) spectroscopy has become a promising technique for blood glucose monitoring. However, an appropriate model of spectral response in humans is yet to be determined because of the reliability problem. In this study, 48 subjects were recruited. The subjects' left forearms were scanned using near infrared spectroscopy to obtain NIR spectra. Simultaneously, a blood sample of glucose was drawn. A new method based on Monte Carlo approach is applied for partial least squares (PLS), named as PLS[sub MC], is proposed. A large numbers of models are built from calibration subsets which are randomly selected from the whole calibration set in order to minimize the noises. It is then determining the mean value over the models with high correlation and small prediction errors. The results show that the method can enhance the stability of PLS model. Also, the performance of the PLS[sub MC] shows more accurate prediction results as compared with conventional PLS.
URI: http://hdl.handle.net/10397/6587
ISSN: 0712-4813 (print)
1875-922X (online)
DOI: 10.3233/SPE-2011-0507
Rights: Copyright © 2011 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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