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应用光程校正空间法提升近红外无创生化分析模型性能

Improvement of model performance for near-infrared non-invasive biochemical analysis by pathlength correction space method

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摘要

由于采用血流容积差光谱相减法进行近红外无创生化分析得到的样品光谱光程不定, 很难得到高性能的定标模型, 本文提出采用光程校正空间法来消除光程差异, 提升定标模型性能。首先, 介绍了净信号分析的原理和校正空间的获取方法; 根据血流容积差光谱相减法的特点, 提出了采用光程校正空间获取待测组分净信号的方法。然后, 以含葡萄糖的脂肪乳溶液为例, 通过光程校正空间获取葡萄糖净信号, 建立定标模型。实验结果表明: 相比没有处理光程直接建立的定标模型, 采用光程校正空间后所建立的模型相关系数(R)从0.978 1提升到0.997 7, 定标均方根偏差(RMSEC)从77.52 mg/dL下降到25.02 mg/dL, 交叉验证均方根偏差(RMSECV)从93.01 mg/dL下降到68.22 mg/dL。结果显示,采用光程校正空间的净信号分析能够有效抑制光程差异对定标模型的影响, 为血流容积差光谱相减法的实际应用奠定了基础。

Abstract

As the spectral pathlength obtained by spectral subtraction approach with different flow blood volumes is uncertain in a near-infrared noninvasive biochemical analysis, it is difficult to obtain a high performance calibration model. Therefore, a pathlength correction space method was proposed to eliminate the uncertain and to improve the performance of calibration. Firstly, the principle of Net Analyte Signal (NAS) and how to obtain a correction space were introduced. Then, a new approach to get NAS was proposed using the pathlength correction space according to the features of spectral subtraction approach. Finally, by taking the intralipid with different glucose concentrations for example, the NAS of glucose was acquired by using the pathlength correction space and a calibration model was established. Compared with the Partial Least Square(PLS) model without pathlength correction space, the correlation coefficient has been improved from 0.978 1 to 0.997 7, the Root Mean Square Error of Calibration (RMSEC) from 77.52 mg/dL down to 25.02 mg/dL, and the Root Mean Square Error of Cross Validation (RMSECV) from 93.01 mg/dL down to 68.22 mg/dL. The analysis result verifies that the pathlength correction space can effectively restrain the influence of different pathlengths and the method can set the stage for the practical application of the spectral subtraction approach with different flow blood volumes.

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中图分类号:O433.1;O657.33

DOI:10.3788/ope.20132108.1974

所属栏目:现代应用光学

基金项目:国家863高技术研究发展计划资助项目(No.2012AA022602);国家自然科学基金重点项目(No.60938002);中国科学院知识创新工程领域前沿资助项目(No.Y00232Q100);应用光学国家重点实验室开放基金资助项目(No.Y1Q03FQ113)

收稿日期:2013-01-22

修改稿日期:2013-03-12

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高洪智:中国科学院 长春光学精密机械与物理研究所 应用光学国家重点实验室, 吉林 长春 130033
卢启鹏:中国科学院 长春光学精密机械与物理研究所 应用光学国家重点实验室, 吉林 长春 130033
丁海泉:中国科学院 长春光学精密机械与物理研究所 应用光学国家重点实验室, 吉林 长春 130033
陈思唯:吉林大学 化学学院, 吉林 长春 130012

联系人作者:高洪智(ghonzi@163.com)

备注:高洪智(1984-), 男, 河南洛阳人, 博士, 助理研究员, 2005年于华中科技大学获得学士学位, 2011年于中国科学院长春光学精密机械与物理研究所获得博士学位, 主要从事光谱仪器、光谱技术方面的研究。

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引用该论文

GAO Hong-zhi,LU Qi-peng,DING Hai-quan,CHEN Si-wei. Improvement of model performance for near-infrared non-invasive biochemical analysis by pathlength correction space method[J]. Optics and Precision Engineering, 2013, 21(8): 1974-1980

高洪智,卢启鹏,丁海泉,陈思唯. 应用光程校正空间法提升近红外无创生化分析模型性能[J]. 光学 精密工程, 2013, 21(8): 1974-1980

被引情况

【1】褚小立,陆婉珍. 近五年我国近红外光谱分析技术研究与应用进展. 光谱学与光谱分析, 2014, 34(10): 2595-2605

【2】刘 瑾,蔡子晋,张紫杨,孙 迪,王 文. 光电容积脉搏波无创测量人体血液成分的评估. 光学 精密工程, 2016, 24(6): 1264-1271

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