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    • 7. 发明授权
    • Automatic process for sample selection during multivariate calibration
    • 多变量校准中样品选择的自动过程
    • US06876931B2
    • 2005-04-05
    • US10211142
    • 2002-08-02
    • Alexander D. LorenzTimothy L. RuchtiThomas B. Blank
    • Alexander D. LorenzTimothy L. RuchtiThomas B. Blank
    • A61B5/00G01N21/27G01N21/35G01N31/00
    • A61B5/1455A61B5/14532A61B5/1495G01N21/274G01N21/359
    • A process for enhancing a multivariate calibration through optimization of a calibration data set operates on a large calibration set of samples that includes measurements and associated reference values to automatically select an optimal sub-set of samples that enables calculation of an optimized calibration model. The process is automatic and bases sample selection on two basic criteria: enhancement of correlation between a partner variable extracted from the independent variable and the dependent variable and reduction of correlation between the dependent variable and interference. The method includes two fundamental steps: evaluation, assigning a measurement of calibration suitability to a subset of data; and optimization, selecting an optimal subset of data as directed by the measurement of suitability. The process is particularly applied in enhancing and automating the calibration process for non-invasive measurement glucose measurement but can be applied in any system involving the calculation of multivariate models from empirical data sets.
    • 通过优化校准数据集来增强多变量校准的过程在包括测量和相关参考值的大型校准样本集上进行操作,以自动选择能够计算优化校准模型的最佳样本子集。 该过程是自动的,并且基于两个基本标准的基础样本选择:增强从独立变量提取的伴随变量与因变量之间的相关性,并降低因变量与干扰之间的相关性。 该方法包括两个基本步骤:评估,将校准适用性的度量分配给数据子集; 和优化,根据适合性的测量指导选择最佳的数据子集。 该过程特别应用于增强和自动化非侵入性测量葡萄糖测量的校准过程,但可以应用于涉及从经验数据集计算多变量模型的任何系统中。
    • 8. 发明授权
    • Targeted interference subtraction applied to near-infrared measurement of analytes
    • 目标干扰减去应用于分析物的近红外测量
    • US06697654B2
    • 2004-02-24
    • US10183906
    • 2002-06-25
    • Alexander D. LorenzThomas B. BlankTimothy L. Ruchti
    • Alexander D. LorenzThomas B. BlankTimothy L. Ruchti
    • A61B500
    • G01N21/4785A61B5/1075A61B5/14532A61B5/1455A61B5/1495A61B5/7264
    • Methods and apparatus for estimating and removing spectral interference improve precision and robustness of non-invasive analyte measurement using Near-infrared (NIR) spectroscopy. The estimation of spectral interference is accomplished, either through multivariate modeling or discrete factor analysis, using a calibration set of samples in which the interference is orthogonal to the analyte signal of interest, or where the shape of the interference is known. Each of the methods results in a multivariate model in which the spectral interference is estimated for a new sample and removed by vector subtraction. Independent models based on classes of sample variability are used to collapse spectral interference and determine more accurately which model is best equipped to estimate the signal of interference in the new sample. Principal components analysis and other commonly known analytical techniques can be used to determine class membership.
    • 用于估计和去除光谱干扰的方法和装置使用近红外(NIR)光谱提高非侵入性分析物测量的精度和鲁棒性。 通过多变量建模或离散因子分析,使用其中干涉与感兴趣的分析物信号正交的样本的校准集合或已知干扰的形状来完成频谱干扰的估计。 每种方法都产生一个多变量模型,其中对新样本估计出光谱干扰,并通过向量减去去除。 使用基于样本变异性类别的独立模型来折叠光谱干扰,并更准确地确定哪种模型最适合估计新样本中的干扰信号。 主成分分析和其他常用分析技术可用于确定类成员资格。
    • 9. 发明授权
    • Intra-serum and intra-gel for modeling human skin tissue
    • 血清内和凝胶内用于建模人体皮肤组织
    • US06475800B1
    • 2002-11-05
    • US09502877
    • 2000-02-10
    • Kevin H. HazenJames Matthew WelchStephen F. MalinTimothy L. RuchtiAlexander D. LorenzTamara L. TroySuresh ThennadilThomas B. Blank
    • Kevin H. HazenJames Matthew WelchStephen F. MalinTimothy L. RuchtiAlexander D. LorenzTamara L. TroySuresh ThennadilThomas B. Blank
    • G01N3100
    • G01N21/274A61B5/0075A61B5/1075A61B5/14532A61B5/1455A61B5/1495A61B5/7264A61B2560/0223A61B2560/0233G01N21/359G01N21/4785G01N21/49Y10T436/10
    • The invention provides a class of samples that model the human body. This family of samples is based upon emulsions of oil in water with lecithin acting as the emulsifier. These solutions that have varying particle sizes may be spiked with basis set components (albumin, urea and glucose) to simulate skin tissues further. The family of samples is such that other organic compounds such as collagen, elastin, globulin and bilirubin may be added, as can salts such as Na+, K+ and Cl−. Layers of varying thickness with known index of refraction and particle size distributions may be generated using simple crosslinking reagents, such as collagen (gelatin). The resulting samples are flexible in each analyte's concentration and match the skin layers of the body in terms of the samples reduced scattering and absorption coefficients, &mgr;ms and &mgr;ma. This family of samples is provided for use in the medical field where lasers and spectroscopy based analyzers are used in treatment of the body. In particular, knowledge may be gained on net analyte signal, photon depth of penetration, photon radial diffusion, photon interaction between tissue layers, photon density (all as a function of frequency) and on instrument parameter specifications such as resolution and required dynamic range (A/D bits required). In particular, applications to delineate such parameters have been developed for the application of noninvasive glucose determination in the near-IR region from 700 to 2500 nm with an emphasis on the region 1000 to 2500 nm (10,000 to 4,000 cm−1).
    • 本发明提供了一类对人体进行建模的样品。 该样品系基于水中的油与卵磷脂作为乳化剂的乳液。 具有不同粒径的这些溶液可以加入基础组分(白蛋白,尿素和葡萄糖)以进一步模拟皮肤组织。 样品家族可以加入诸如胶原,弹性蛋白,球蛋白和胆红素的其它有机化合物,也可以加入诸如Na +,K +和Cl-的盐。 可以使用简单的交联试剂如胶原(明胶)产生具有已知折射率和粒度分布的不同厚度的层。 所得样品在每种分析物的浓度上是灵活的,并且根据样品减少的散射和吸收系数,妈妈和玛玛来匹配身体的皮肤层。 该样品系列用于医疗领域,其中使用激光和基于光谱的分析仪来治疗身体。 特别地,可以获得关于净分析物信号,光子穿透深度,光子径向扩散,组织层之间的光子相互作用,光子密度(全部作为频率的函数)以及仪器参数规格(例如分辨率和所需动态范围) 需要A / D位)。 特别地,已经开发了描绘这些参数的应用,用于在700至2500nm的近红外区域中应用非侵入性葡萄糖测定,重点在1000至2500nm(10,000至4000cm -1)的区域。