成像体模
红外线的
材料科学
光谱学
光学
红外光谱学
生物医学工程
近红外光谱
核磁共振
医学
物理
量子力学
作者
Jianming Xue,Liming Ye,Chunyan Li,Mingxiang Zhang,Peng Li
出处
期刊:Optik
[Elsevier]
日期:2018-10-01
卷期号:170: 30-36
被引量:11
标识
DOI:10.1016/j.ijleo.2018.05.050
摘要
Diabetes is one of the most serious metabolic diseases worldwide, and frequent monitoring of blood glucose is an essential part of diabetic management. However, a significant drawback of current monitoring methods was destructive and time-consuming. To meet this need, this study was to develop a method for rapid and noninvasive blood glucose assay in a skin tissue phantom by Near-Infrared spectroscopy (NIRS) and Raman spectroscopy. With partial least-squares (PLS) regression method, the multivariate calibration models of NIRS were generated and optimized individually by considering spectral region, spectral pretreatment methods and latent variables (LVs). The optimal NIR model was established with root mean square error of cross-validation (RMSECV) of 0.114, root mean square error of validation (RMSEP) of 0.061, correlation coefficient (R) of 0.9933, and residual predictive deviation (RPD) of 12.2, respectively. The validation results demonstrated that NIRS could be applied for rapid and noninvasive blood glucose assay.
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