NDLI: Wavenumbers Combination Optimization for NIRS Analysis of Glucose in Human Serum

Content Provider	IEEE Xplore Digital Library
Author	Jun Xie Tao Pan Jiemei Chen Huazhou Chen Guoqiang Jiang Lingling Wu
Copyright Year	2010
Abstract	The wavenumbers combination selection of near infrared spectroscopy (NIRS) analysis was very important for improving model prediction effect, reducing model complexity and designing special NIRS instruments with high signal noise ratio. Based on the prediction effect of single wavenumber linear regression model, a wavenumbers combination selection method of NIRS analysis of glucose in human serum was developed. 25 wavenumbers with good prediction effect were selected. All wavenumber combinations of the twenty-five wavenumbers were used to establish multiple linear regression (MLR) models respectively. According to the prediction effect, the optimal MLR model was the eleven wavenumbers combination of 7340, 7328, 7311, 7253, 7251, 7234, 7228, 7220, 7218, 7207, 7203 (cm-1), the corresponding root mean squared error of predication (RMSEP) was 0.384 mmol/L. And the prediction effect was obvious better than one of partial least squares (PLS) model. These indicated that the wavenumbers combination selection method based on the prediction effect of single wavenumber linear regression model could be applied to the NIRS analysis and could provide valuable reference for designing minitype special NIRS instruments.
Starting Page	1
Ending Page	4
File Size	339903
Page Count	4
File Format	PDF
ISBN	9781424449637
DOI	10.1109/SOPO.2010.5504083
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Instruments Linear regression Noise reduction Humans Predictive models Infrared spectra Signal analysis Sugar Signal design Signal to noise ratio
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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