Classification of diabetes and measurement of blood glucose concentration noninvasively using near infrared spectroscopy

Developing noninvasive blood glucose monitoring method is an to immense need to alleviate the pain and suffering of diabetics associated with the frequent pricking of skin for taking blood sample. A hybrid algorithm for multivariate calibration is proposed to improve the prediction performance of classification of diabetes and measurement of blood glucose concentration by near infrared (NIR) spectroscopy noninvasively. The algorithm is based on wavelet prism modified uninformative variable elimination approach (WP-mUVE) combined with least squares support vector machine (LSSVM), named as WP-mUVE-LSSVM. The method is successfully applied to diabetic classification experiment (in vivo) and blood glucose concentration measurement experiment (in vivo) respectively. Human tongue is selected as the measuring site in this study. To evaluate effectiveness of pretreatment method and quality of calibration models, several usually used pretreatment methods and kernel functions of LSSVM are introduced comparing with our method. Higher quality data is obtained by our pretreatment method owing to the elimination of varying background and noise of spectra data simultaneously. Better prediction accuracy and adaptability are obtained by LSSVM model with radial basis kernel function. The results indicate that WP-mUVE-LSSVM holds promise for the classification of diabetes and measurement of blood glucose concentration noninvasively based on human tongue using NIR spectroscopy.     

A nonlinear model for calibration of blood glucose noninvasive measurement using near infrared spectroscopy

In order to improve prediction accuracy of calibration in human blood glucose noninvasive measurement using near infrared (NIR) spectroscopy, a modified uninformative variable elimination (mUVE) method combined with kernel partial least squares (KPLS), named as mUVE–KPLS, is proposed as an alternative nonlinear modeling strategy. Under the mUVE method, high-frequency noise and matrix background can be eliminated simultaneously, which provide a optimized data for calibration in sequence; under the kernel trick, a nonlinear relationship of response variable and predictor variables is constructed, which is different with PLS that is a complex model and inappropriate to describe the underlying data structure with significant nonlinear characteristics. Two NIR spectra data of basic research experiments (simulated physiological solution samples experiment in vitro and human noninvasive measurement experiment in vivo) are introduced to evaluate the performance of the proposed method. The results indicate that, after elimination high-frequency noise and matrix background from optical absorption of water in NIR region, a high-quality spectra data is employed in calibration; and under the selection of kernel function and kernel parameter, the best prediction accuracy can be got by KPLS with Gaussian kernel compared with Spline-PLS and PLS. It is encouraging that mUVE–KPLS is a promising nonlinear calibration strategy with higher prediction accuracy for blood glucose noninvasive measurement using NIR spectroscopy.     

六味地黄丸指纹图谱的近红外光谱分析方法的建立

建立了一种近红外光谱测定六味地黄丸指纹图谱的方法。应用毛细管电泳法建立六味地黄丸指纹图谱,计算其相似度,同时测定其近红外光谱,建立六味地黄丸指纹图谱相似度与近红外光谱之间的数学模型。通过对模型的优化,建模集样品的相关系数(r)、校正标准差和平均相对误差分别为0.9046,0.058和6.12%,表明六味地黄丸指纹图谱相似度实测值与预测值之间有较好的线性关系。研究结果表明以基于指纹图谱的近红外光谱法用于六味地黄丸的质量控制具有可行性。     

氯化钠近红外光谱检测技术研究

氯化钠(NaCl)近红外光谱分析在生物医学上有着重要的意义。钠离子(Na+)是人体血液中电解质的主要成分,而电解质有助于维持身体的酸碱平衡。采用近红外光谱技术测量氯化钠浓度,在分析钠离子近红外光谱检测机理的基础上,选定波长建立了NaCl浓度线性回归预测模型,同时为了减小温度对水吸收的扰动,使用选定光谱区建立偏最小二乘(PLS)非线性回归模型。结果表明所建立的非线性校正模型决定系数(R2)=99.82%,交叉验证均方误差(RMSECV)=14.5,剩余预测偏差(RPD)=23.7。完全满足日常生化检测精度要求,该技术可以应用于医院实验室钠离子浓度定量分析。     

Using quantum theory to improve measurement precision

Progress in science is inextricably linked with how well we can observe the world around us. It is by making increasingly better measurements that scientific theories are tested and refined. In this article we address the question of what the ultimate limit to measurement precision is and how it could be achieved in the laboratory. We focus on how, by making use of quantum theory, it is possible to make better measurements than anything that can be achieved with classical techniques. This opens the door to an array of new technologies and could help answer some of science's most engaging questions.     

基于近红外光谱的高精度测温系统

目前红外测温方法难以消除复杂环境下外来辐射的干扰,导致测温精度低,设计了一种高精度的红外测温系统。该系统提出了由宽带滤光片和三级干涉滤光器结合的滤光方法,根据该方法对高温物体发出的近红外光谱进行滤光,将高温背景光和环境干扰光滤掉,得到两个单色光谱,经红外探测器接收获得其辐射功率比,通过计算得出物体温度。该系统透过的单色光谱带宽仅有1nm,将透射光谱以外的背景光辐射和环境光源辐射抑制达8个数量级,降低了因被测对象周围环境升温引起的测温误差,提高测温系统的精度。最后通过实验验证了该测温系统的可行性,精度达0.2%。     

近红外光谱用于杉木木材强度分等的研究

利用近红外光谱技术对木材强度分等进行了研究.选择 1000～1400 nm波段,结合偏最小二乘法,在木材强度和近红外光谱数据间建立了校正模型,校正模型的相关系数(r)为0.89,校正标准误差(SEC)为6.30 MPa.利用校正模型对35个未知样品的强度进行预测,根据近红外预测值和实测值分别对木材样品进行分等,A级预测...     

一种基于近红外光谱技术的熊胆粉鉴别方法

建立了一种基于近红外光谱分析技术的方法,对熊胆粉的真伪进行了签别,并对掺伪品中熊胆粉的掺入比例进行了定量分析.采集了四处不同产地的30份熊胆粉样品,六份猪胆粉份样品,以及65份按不同比例混合的熊胆粉与猪胆粉的混合样品的近红外光谱,对所采集的样品光谱进行主成分分析,观察到熊胆及其伪品和掺伪品之间存在明显的界限,不同产地的...     

近红外光谱技术用于无创生化检验研究的进展

20世纪90年代初,近红外光谱技术在人体无创生化检验方面的潜力逐渐获得重视。然而,人体是一个极其复杂多变的检测对象,因此虽然各研究小组在实验模拟和离体分析方面取得了一定成果,但在临床应用上始终没有实质性突破。文章讨论了目前阻碍近红外光谱技术实现临床意义上的人体无创生化检验的关键问题,即信号微弱、组织背景干扰、血流容积变化问题。将国际上现有的近红外无创生化检验研究工作的思路按照分析方法大致归为两类,即经典近红外分析法和扣除组织背景干扰分析法。详细介绍了这两类研究思路各自的研究现状,并认为在现有条件下第二类思路更有希望取得临床可以应用的结果。     

一种近红外光谱特征子区间选择新算法

为了简化光谱模型和提高模型精度,在传统遗传算法中引入Metropolis接受准则,提出了一种新的模拟退火-遗传区间选择算法(SAA-GA-iPLS),用于快速提取近红外光谱特征子区间,采用偏最小二乘法(PLS)建立近红外光谱模型。以黄瓜叶近红外光谱数据及其类胡萝卜素含量为例,将全光谱分为40个区间,模拟退火-遗传算法能快速优选出7个子区间(分别为第3,5,14,18,21,32,33子区间),在所选7个子区间的基础上建立了黄瓜叶类胡萝卜素PLS光谱模型。与传统遗传算法的比较结果表明:无论是建模效果还是算法执行效率,模拟退火-遗传算法均优于传统遗传算法。     

近红外光谱法快速测定羊草干草品质的研究

试验共采集我国北方不同区域、不同生育期、不同干燥方式的羊草干草150份,利用近红外漫反射光谱(NIRS)技术,采用偏最小二乘回归算法(PLS),在国内首次建立了适配范围广的羊草干草的粗蛋白(CP)、中性洗涤纤维(NDF)和酸性洗涤纤维(ADF)的校正模型,并对模型的预测能力进行了验证.结果表明,所建模型的预测结果与常规...     

基于近红外光谱技术的人体血糖浓度无创检测系统的研制

开发了一种小型化人体血糖浓度无创检测系统,该系统可实现人体血糖浓度的快速、实时、无创检测,主要由嵌入式系统、夹具、光源系统和微型光栅光谱仪四部分组成。提出了一种光源稳压驱动电路方案,可满足多种光谱采集条件对光源的要求。同时提出了一种一体化夹具设计方案,不仅简化了系统的光学结构,而且提高了测量条件的可重复性。分别用小波去噪和核偏最小二乘法对采集的光谱数据进行预处理和数学建模,并对系统进行性能评价,血糖浓度预测值与标准值的相关系数为0.95,预测均方根误差为0.6mmol.L-1,系统的重复性较好。     

基于可见-近红外光谱技术的润滑油含水量无损检测方法研究

研究了基于可见-近红外光谱技术的发动机润滑油含水量快速检测方法。在获取光谱信息的基础上,提出了采用不同的光谱建模方法以提高检测精度和简化分析计算。分别采用主成分分析(PCA)和连续投影算法(SPA)方法进行模型输入变量的提取。SPA最终选择了476,483,544,925,933,938,952,970和974nm共9个波长为最优变量。基于SPA选择的变量,分别应用偏最小二乘回归(PLSR)和多元线性回归(MLR)建模。效果均优于全波段PLSR模型和PCA-PLSR模型。说明SPA选择的有效变量能够包含最重要的全波段光谱信息,同时可以去除无用的信息变量。为了进一步提高检测效果,采用LS-SVM分别基于SPA选择后的有效变量和全波段光谱进行建模。两个模型的预测确定系数(Rp2)均在0.9以上。SPA-LS-SVM的效果要优于全波段LS-SVM模型的效果。SPA-LS-SVM模型的Rp2达到了0.983,剩余预测偏差(RPD)值为6.963。表明可见-近红外光谱可以用于发动机润滑油含水量的检测。     

尿微量白蛋白的可见-近红外光谱检测

尿微量白蛋白是临床上检测肾损伤最可靠的诊断指标.为实现尿微量白蛋白快速无试剂检测,本文采用多光程方式得到207例尿液样品可见-近红外双波段的多光程光谱,基于多光程光谱的非线性特性,获得更多样品成分含量的信息.在首先进行PLS建模的基础上,使用PLS-ANN建模方法引入非线性信息,对样本的可见-近红外波段多光程光谱与尿微...     

红外反射光谱的原理和方法

固体的光学性质是凝聚态物理学中的一类重要问题,它可以用一系列的光学常数进行描写.在实验上,最常用的方法是,测量材料在一个尽可能宽的频率范围内的正入射反射率,然后通过Kramers-Kronig(KK)变换的方法来得到光学常数.文章介绍了傅里叶变换红外反射光谱的原理、仪器组成和一种原位蒸发镀膜技术.这样的方法可以很好地测量包括小尺寸和不规则样品在内的材料从数个毫电子伏至数个电子伏范围内的反射率,因而在研究固体的各种不同的单粒子激发（或集体激发）中起重要的作用.     

精密红外辐射计测量模块研究北大核心CSCD

红外辐射计用于红外热像仪测试设备的校准。介绍了一种用于红外辐射计的测量模块及方法。设计了采样保持的测量方案,通过参考信号生成采样脉冲,并将采样点设置在每个信号周期的1/4相位处,能显著提高微弱信号的测量能力。对于35℃的黑体辐射信号,通过与现有方案的对比实验,测量信号强度可提高57.6%;在红外热像仪测试设备背景温度为22℃条件下,通过与现有仪器的对比测试,测量信号精度可提升50%以上。     

利用近红外光谱鉴别纺织用竹纤维和麻纤维

利用近红外光谱技术对竹原纤维、竹粘胶纤维和苎麻纤维进行了快速定性鉴别研究.首先扫描3种纤维的近红外光谱,利用化学计量学分析软件,对谱图进行一阶导数预处理,建立不同纤维的光谱数据库,并分别建立竹原纤维、竹粘胶纤维和苎麻纤维的判别模型.利用判别模型,对未知样品进行判别.结果表明,近红外光谱可以在不破坏样品的情况下,可以快速鉴别竹原纤维、竹粘胶纤维和苎麻纤维.     

Near infrared spectroscopy assessment of the glucose solution processed by ultrasonic cavitation

The near infrared (NIR) absorption was investigated on the glucose aqueous solutions with various optical pathlengths (PLs) and processed by ultrasonic cavitation. In water, the strong absorption peak at a wavelength of 1430 nm, appeared in the case of short PL, was separated into several peaks in the case of wide PL due to increasing the number of H(2)O clusters. In a d(+) glucose solution, it was seen that NIR absorption was reduced at peculiar wavelengths of 970 nm and 1130 nm and its profile changed in a capricious manner in the region from 1300 nm to 1600 nm. The cavitation generated lots of OH(-) ion in water and made the capricious absorption profile regularly graded with the cavitation time toward less-absorptive direction. These effects are supposed to be caused by the dipole moments of H(2)O clusters arranged by the interaction between them and generated basic OH ions. The statistical principal component regression (PCR) and partial least-squares (PLS) regression demonstrated that the treatment of UC was helpful to enhance the glucose sensitivity.     

Remote measurement of volcanic gases by Fourier transform infrared spectroscopy

Received: 25 March 1998