Comparison of three chemometrics methods for near-infrared spectra of glucose in the whole blood

Hongyan Zhang; Dong Ding; Xin Li; Yu Chen; Yuguo Tang

doi:10.1117/12.572350

10 January 2005 Comparison of three chemometrics methods for near-infrared spectra of glucose in the whole blood

Hongyan Zhang, Dong Ding, Xin Li, Yu Chen, Yuguo Tang

Proceedings Volume 5640, Infrared Components and Their Applications; (2005) https://doi.org/10.1117/12.572350
Event: Photonics Asia, 2004, Beijing, China

Abstract

Principal Component Regression (PCR), Partial Least Square (PLS) and Artificial Neural Networks (ANN) methods are used in the analysis for the near infrared (NIR) spectra of glucose in the whole blood. The calibration model is built up in the spectrum band where there are the glucose has much more spectral absorption than the water, fat, and protein with these methods and the correlation coefficients of the model are showed in this paper. Comparing these results, a suitable method to analyze the glucose NIR spectrum in the whole blood is found.

Citation Download Citation

Hongyan Zhang, Dong Ding, Xin Li, Yu Chen, and Yuguo Tang "Comparison of three chemometrics methods for near-infrared spectra of glucose in the whole blood", Proc. SPIE 5640, Infrared Components and Their Applications, (10 January 2005); https://doi.org/10.1117/12.572350

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