血液与尿液成分的多光程光谱法检测
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摘要
光谱分析方法以其灵敏、快速、准确的检测特点,在各个领域得到广泛应用。血液和尿液的成分含量是判断人体健康状况的客观依据,低成本血液和尿液成分快速检测方法具有重要的学术意义和社会价值。基于多光程光谱比单一光程光谱能够提供更多样本成分含量信息从而提高测量精度的理论,对多光程光谱法血液及尿液成分检测进行了初步研究和探索。
设计并搭建了自动多光程光谱检测系统以获得多光程光谱数据。该系统由自动微位移装置、光谱仪和微机(上位机)构成,通过编写的上位机VB.net程序及微控制器控制程序协同工作,精确控制自动微位移装置微小位移,实现了多光程光谱数据的自动采集。
在血液成分含量检测实验中,采集200例血清样本近红外多光程光谱数据,并对样本葡萄糖、总胆固醇、总蛋白、白蛋白含量进行建模分析,r2分别为0.8686、0.9432、0.8953和0.8993, RMSEP分别为0.6792mmol/L、0.2064mmol/L、2.8469g/L和1.7942g/L。多光程光谱提取特征波长的初步研究表明光程分段挑选波长方法的建模效果最优,可将光谱数据维数缩减为原始数据的1/40,对多光程光谱降维方法的研究有一定的积极意义。
在光谱尿液成分检测实验中,选择肾脏损伤敏感指标尿微量白蛋白作为检测对象。采集标准品配制的27个尿样和207例实际尿样多光程可见-近红外光谱信息。配制尿样使用可见-近红外双波段多光程光谱建立的回归模型优于使用单一波段建模,r2达0.9905,最大预测绝对误差为7.56mg/L。实际尿样建模中充分考虑光谱数据的非线性因素,使用PLS-ANN联立建模,r2为0.9511,RMSEP为5.02 mg/L,提高了定量分析精度。
课题设计自动多光程检测系统以减小误操作发生的几率,提高了实验效率和准确度,具有良好的稳定性和可重复性,并通过初步对多光程光谱数据建模分析、特征提取等数据挖掘手段的研究,可以较准确的预测血液中葡萄糖、总胆固醇、总蛋白、白蛋白四种成分和尿液中微量白蛋白的含量,为进一步探索血液和尿液多光程光谱采集分析的检测方法奠定了基础。
Spectral analysis method, with sensitive, rapid and accurate features, is widely used in various fields. The concentration level of blood and urine components is the main judgment basis of human health condition. Low-cost and rapid detection of blood and urine components has important academic significance and social value. In theory, the multiple optical path length spectra, with the nonlinear feature, can provide more information of the sample than single optical path length spectra and can improve the accuracy of measurement, using the abundant information. Based on this theory, the preliminary research and exploration on the measurement of blood and urine components was carried out in this work.
To obtain the multiple optical path length spectra data, the automatic detection system was established. The system consists of an automatic micro-displacement device, two spectrometers and a PC. By the cooperative work of the software designed based on VB.net language and the micro-controller, the minute optical length can be changed accurately and stably and the data obtaining processing can be performed automatically.
In the measuring experiment of blood components, near-infrared multiple optical path length spectra of 200 serum samples were collected. The models of glucose, total cholesterol, total protein and albumin were established. The r2 of prediction are 0.8686, 0.9432, 0.8953 and 0.8993, and the RMSEP are 0.6792 mmol/L, 0.2064 mmol/L, 2.8469 g/L and 1.7942 g/L, respectively. The result of the preliminary study on the feature extraction shows that picking up the special wavelengths from group of optical path length has the best performance. The dimension of spectral data decreases to 1/40 of the original data. This method has the positive significance to the modeling of multiple optical path length spectra.
In the measuring experiment of urine components, UMALB, the sensitive indicator of renal injury, was selected as the measuring object. 27 standard samples of urine and 207 human urine samples were acquired. The modeling results of standard samples show that the model established by both visible and near-infrared spectral information is better than that using a single band. Its r2 is up to 0.9905, and the maximum absolute prediction error is 7.56mg/L. Considering the nonlinear factors of spectral data, the PLS-ANN modeling method was involved to increase the accuracy of quantitative analysis. The r2 of the human urine samples is 0.9511, and RMSEP is 5.02 mg/L.
This detection system designed in this work reduced the probability of misoperation, and improved the efficiency and accuracy of experiments greatly. The prediction accuracy of glucose, total cholesterol, total protein, albumin and UMALB concentration is improved according to the preliminary study of data mining method, such as model establishment and feature extraction, which is basis of the follow-up blood and urine multiple optical path length spectra collection and analysis.
设计并搭建了自动多光程光谱检测系统以获得多光程光谱数据。该系统由自动微位移装置、光谱仪和微机(上位机)构成,通过编写的上位机VB.net程序及微控制器控制程序协同工作,精确控制自动微位移装置微小位移,实现了多光程光谱数据的自动采集。
在血液成分含量检测实验中,采集200例血清样本近红外多光程光谱数据,并对样本葡萄糖、总胆固醇、总蛋白、白蛋白含量进行建模分析,r2分别为0.8686、0.9432、0.8953和0.8993, RMSEP分别为0.6792mmol/L、0.2064mmol/L、2.8469g/L和1.7942g/L。多光程光谱提取特征波长的初步研究表明光程分段挑选波长方法的建模效果最优,可将光谱数据维数缩减为原始数据的1/40,对多光程光谱降维方法的研究有一定的积极意义。
在光谱尿液成分检测实验中,选择肾脏损伤敏感指标尿微量白蛋白作为检测对象。采集标准品配制的27个尿样和207例实际尿样多光程可见-近红外光谱信息。配制尿样使用可见-近红外双波段多光程光谱建立的回归模型优于使用单一波段建模,r2达0.9905,最大预测绝对误差为7.56mg/L。实际尿样建模中充分考虑光谱数据的非线性因素,使用PLS-ANN联立建模,r2为0.9511,RMSEP为5.02 mg/L,提高了定量分析精度。
课题设计自动多光程检测系统以减小误操作发生的几率,提高了实验效率和准确度,具有良好的稳定性和可重复性,并通过初步对多光程光谱数据建模分析、特征提取等数据挖掘手段的研究,可以较准确的预测血液中葡萄糖、总胆固醇、总蛋白、白蛋白四种成分和尿液中微量白蛋白的含量,为进一步探索血液和尿液多光程光谱采集分析的检测方法奠定了基础。
Spectral analysis method, with sensitive, rapid and accurate features, is widely used in various fields. The concentration level of blood and urine components is the main judgment basis of human health condition. Low-cost and rapid detection of blood and urine components has important academic significance and social value. In theory, the multiple optical path length spectra, with the nonlinear feature, can provide more information of the sample than single optical path length spectra and can improve the accuracy of measurement, using the abundant information. Based on this theory, the preliminary research and exploration on the measurement of blood and urine components was carried out in this work.
To obtain the multiple optical path length spectra data, the automatic detection system was established. The system consists of an automatic micro-displacement device, two spectrometers and a PC. By the cooperative work of the software designed based on VB.net language and the micro-controller, the minute optical length can be changed accurately and stably and the data obtaining processing can be performed automatically.
In the measuring experiment of blood components, near-infrared multiple optical path length spectra of 200 serum samples were collected. The models of glucose, total cholesterol, total protein and albumin were established. The r2 of prediction are 0.8686, 0.9432, 0.8953 and 0.8993, and the RMSEP are 0.6792 mmol/L, 0.2064 mmol/L, 2.8469 g/L and 1.7942 g/L, respectively. The result of the preliminary study on the feature extraction shows that picking up the special wavelengths from group of optical path length has the best performance. The dimension of spectral data decreases to 1/40 of the original data. This method has the positive significance to the modeling of multiple optical path length spectra.
In the measuring experiment of urine components, UMALB, the sensitive indicator of renal injury, was selected as the measuring object. 27 standard samples of urine and 207 human urine samples were acquired. The modeling results of standard samples show that the model established by both visible and near-infrared spectral information is better than that using a single band. Its r2 is up to 0.9905, and the maximum absolute prediction error is 7.56mg/L. Considering the nonlinear factors of spectral data, the PLS-ANN modeling method was involved to increase the accuracy of quantitative analysis. The r2 of the human urine samples is 0.9511, and RMSEP is 5.02 mg/L.
This detection system designed in this work reduced the probability of misoperation, and improved the efficiency and accuracy of experiments greatly. The prediction accuracy of glucose, total cholesterol, total protein, albumin and UMALB concentration is improved according to the preliminary study of data mining method, such as model establishment and feature extraction, which is basis of the follow-up blood and urine multiple optical path length spectra collection and analysis.
引文
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[2] Enejder A M K,Scecina T G,Oh J,et al. Raman spectroscopy for noninvasive glucose measurements,Journal of Biomedical Optics,2005,10(3):31114~31119.
[3] Katsuhiko Maruo,Mitsuhiro Tsurugi,Jakusei Chin,et al. Noninvasive Blood Glucose Assay Using a Newly Developed Near-Infrared System,IEEE Jouranal of Selected Topics in Quantum Electronics,2003,9(2):322~329.
[4]李刚,王焱,李秋霞,动态光谱法对提高近红外无创血液成份检测精度的理论分析,红外与毫米波学报,2006,25(5):345~348.
[5]张志勇,门剑龙,李刚,等.动态光谱法用于人体血红蛋白浓度的无创测量,光谱学与光谱分析,2010,30(1):150~153.
[6]雷猛,冯新泸,何滔,广义二维相关光谱技术及其应用,光谱实验室,2008,25(5):996~1002.
[7]刘浩,黄艳萍,高鸿彬,等.含氮芳香类药物的近红外及二维相关光谱分析,计算机与应用化学,2008,25(6):724~728.
[8] Goetz A F H,Rowan L C,Geologic remote sensing,Science,1981,221:81~791.
[9] Goetz A F H,Remote,Three decades of hyperspectral remote sensing of the Earth: A personal view,Sensing of Environment,2009,113:S5~S16.
[10]Wold S,Albano C,Dunn M,et al. Pattern recognition: finding and using regularities in multivariate data,Food Research and Data Analysis,Applied Science,1983:147~188.
[11]丁丽,相玉红,张卓勇,近红外光谱定量预测奶粉中三聚氰胺的含量,首都师范大学学报(自然科学版),2010,31(1):26~29.
[12]王俊,陈国庆,魏柏林,等.基于BP神经网络的日落黄溶液荧光光谱的研究,光学技术,2009,35(6):868~871.
[13]吴新生,谢益民,支持向量机回归法在近红外光谱测定植物纤维原料中甲氧基含量中的应用,化学分析计量,2009,18(2):17~20.
[14]吴桂芳,黄凌霞,何勇,葡萄浆果糖度可见/近红外光谱检测的研究,光谱学与光谱分析,2008,28(9):2090~2093.
[15]方利民,林敏,基于独立分量和神经网络的近红外多组分分析方法,分析化学,2008,36(6):815~818.
[16]黄康,汪辉君,徐惠荣,基于最小二乘支持向量机的番茄汁糖酸度分析研究,光谱学与光谱分析,2009,29(4):931~934.
[17]吴迪,何勇,冯水娟,基于LS-SVM的红外光谱技术在奶粉脂肪含量无损检测中的应用,红外与毫米波学报,2008,27(3):180~184.
[18]侯瑞,吉海彦,张录达,基于OSC-PLS算法对大麦蛋白质含量进行定量分析的研究,光谱学与光谱分析,2009,29(7):1840~1843.
[19]陈全胜,郭志明,赵杰文,等.基于净分析物预处理算法的绿茶中儿茶素的近红外光谱定量分析,红外与毫米波学报,2009,28(5):357~361.
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