DocumentCode
1477190
Title
Chemometric Approach for Improving VCSEL-Based Glucose Predictions
Author
Fard, Sahba Talebi ; Chrostowski, Lukas ; Kwok, Ezra ; Amann, Markus-Christian
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC, Canada
Volume
57
Issue
3
fYear
2010
fDate
3/1/2010 12:00:00 AM
Firstpage
578
Lastpage
585
Abstract
Optical methods are one of the painless and promising techniques that can be used for blood glucose predictions for diabetes patients. The use of thermally tunable vertical cavity surface-emitting lasers (VCSELs) as the light source to obtain blood absorption spectra, along with the multivariate technique partial least squares for analysis and glucose estimation, has been demonstrated. With further improvements by using data preprocessing and two VCSELs, we have achieved a clinically acceptable level in the physiological range in buffered solutions. The results of previous experiments conducted using white light showed that increasing the number of wavelength intervals used in the analysis improves the accuracy of prediction. The average prediction error, using absorption spectra from one VCSEL in aqueous solution, is about 1.2 mM. This error is reduced to 0.8 mM using absorption spectra from two VCSELs. This result confirms that increasing the number of VCSELs improves the accuracy of prediction.
Keywords
bio-optics; biochemistry; blood; buffer layers; diseases; laser applications in medicine; laser cavity resonators; least squares approximations; organic compounds; patient monitoring; spectrochemical analysis; surface emitting lasers; absorption spectra; blood absorption spectra; blood glucose predictions; buffered solutions; chemometric approach; data preprocessing; diabetes patients; improving VCSEL-based glucose predictions; multivariate technique partial least squares; thermally tunable vertical cav?? ity surface-emitting lasers; Absorption; Accuracy; Blood; Chemical lasers; Diabetes; Optical buffering; Optical surface waves; Sugar; Tunable circuits and devices; Vertical cavity surface emitting lasers; Chemometrics for glucose prediction; optical glucose monitoring; real-time glucose monitoring; Blood Glucose; Humans; Lasers; Magnetic Resonance Spectroscopy; Models, Biological; Monitoring, Physiologic; Predictive Value of Tests; Reproducibility of Results; Signal Processing, Computer-Assisted;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/TBME.2009.2032160
Filename
5268215
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