公开(公告)号：US06501982B1

公开(公告)日：2002-12-31

申请号：US09487236

申请日：2000-01-19

申请人： Timothy L. Ruchti ,  Suresh Thennadil ,  Stephen F. Malin ,  Jessica Rennert

发明人： Timothy L. Ruchti ,  Suresh Thennadil ,  Stephen F. Malin ,  Jessica Rennert

IPC分类号： A61B600

CPC分类号： A61B5/441 ,  A61B5/0059 ,  A61B5/0075 ,  A61B5/1075 ,  A61B5/14532 ,  A61B5/14546 ,  A61B5/1455 ,  A61B5/7264 ,  A61B5/7267 ,  A61B2560/0223 ,  G01N21/359 ,  G01N21/4785

摘要： Noninvasive instrumentation and procedures have been developed for estimating the apparent age of human and animal subjects based on the irradiation of skin tissue with near-infrared light. The method of age estimation provides additional information about primary sources of systematic tissue variability due to chronological factors and environmental exposure. Therefore, categorization of subjects on the basis of the estimated apparent age is suitable for further spectral analysis and the measurement of biological and chemical compounds, such as blood analytes. Furthermore, age determination of subjects has particular benefit in assessment of therapies used to reduce the effects of ageing in tissue and measurement of tissue damage.

摘要翻译： 已经开发了非侵入性仪器和程序，用于基于用近红外光照射皮肤组织来估计人和动物受试者的表观年龄。 年龄估计的方法提供了关于由于时间因素和环境暴露引起的系统组织变异性的主要来源的附加信息。 因此，根据估计的表观年龄对受试者的分类适用于进一步的光谱分析和生物和化学化合物如血液分析物的测量。 此外，受试者的年龄确定在评估用于减少组织中老化的影响和测量组织损伤的疗法方面特别有益。

公开(公告)号：US06493566B1

公开(公告)日：2002-12-10

申请号：US09487733

申请日：2000-01-19

申请人： Timothy L. Ruchti ,  Stephen F. Malin ,  Suresh Thennadil ,  Jessica Rennert ,  Glenn Aaron Kees

发明人： Timothy L. Ruchti ,  Stephen F. Malin ,  Suresh Thennadil ,  Jessica Rennert ,  Glenn Aaron Kees

IPC分类号： A61B5100

CPC分类号： G01N21/4785 ,  A61B5/0059 ,  A61B5/0075 ,  A61B5/1075 ,  A61B5/14532 ,  A61B5/14546 ,  A61B5/1455 ,  A61B5/441 ,  A61B5/7203 ,  A61B5/7264 ,  A61B5/7267 ,  A61B2560/0223 ,  G01N21/359

摘要： Instrumentation and procedures for noninvasively determining the sex of human and animal subjects in vivo have been developed based on the irradiation of skin tissue with near infrared light. The method of sex determination provides additional information about primary sources of systematic tissue variability, namely, the thickness of the dermis and the subcutaneous fat. Categorization of subjects on the basis of the determination is therefore suitable for further spectral analysis and the measurement of biological and chemical compounds, such as blood analytes.

摘要翻译： 已经基于用近红外光照射皮肤组织来开发用于非侵入性地确定人体和动物受试者的性别的仪器和程序。 性别确定的方法提供了关于系统组织变异性的主要来源的额外信息，即真皮和皮下脂肪的厚度。 因此，在确定的基础上对受试者的分类适用于进一步的光谱分析和生物化学化合物如血液分析物的测量。

公开(公告)号：US06475800B1

公开(公告)日：2002-11-05

申请号：US09502877

申请日：2000-02-10

申请人： Kevin H. Hazen ,  James Matthew Welch ,  Stephen F. Malin ,  Timothy L. Ruchti ,  Alexander D. Lorenz ,  Tamara L. Troy ,  Suresh Thennadil ,  Thomas B. Blank

发明人： Kevin H. Hazen ,  James Matthew Welch ,  Stephen F. Malin ,  Timothy L. Ruchti ,  Alexander D. Lorenz ,  Tamara L. Troy ,  Suresh Thennadil ,  Thomas B. Blank

IPC分类号： G01N3100

CPC分类号： G01N21/274 ,  A61B5/0075 ,  A61B5/1075 ,  A61B5/14532 ,  A61B5/1455 ,  A61B5/1495 ,  A61B5/7264 ,  A61B2560/0223 ,  A61B2560/0233 ,  G01N21/359 ,  G01N21/4785 ,  G01N21/49 ,  Y10T436/10

摘要： 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).

摘要翻译： 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。

公开(公告)号：US06777240B2

公开(公告)日：2004-08-17

申请号：US10241344

申请日：2002-09-11

申请人： Kevin H. Hazen ,  James Matthew Welch ,  Stephen F. Malin ,  Timothy L. Ruchti ,  Alexander D. Lorenz ,  Tamara L. Troy ,  Suresh Thennadil ,  Thomas B. Blank

发明人： Kevin H. Hazen ,  James Matthew Welch ,  Stephen F. Malin ,  Timothy L. Ruchti ,  Alexander D. Lorenz ,  Tamara L. Troy ,  Suresh Thennadil ,  Thomas B. Blank

IPC分类号： G01N3100

CPC分类号： G01N21/274 ,  A61B5/0075 ,  A61B5/1075 ,  A61B5/14532 ,  A61B5/1455 ,  A61B5/1495 ,  A61B5/7264 ,  A61B2560/0223 ,  A61B2560/0233 ,  G01N21/359 ,  G01N21/4785 ,  G01N21/49 ,  Y10T436/10

摘要： 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;'s and &mgr;a. 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).

摘要翻译： 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。 样品家族可以加入其它有机化合物如胶原蛋白，弹性蛋白，球蛋白和胆红素，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柔性的，并且根据样品减少的散射和吸收系数mu和μa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，已经开发出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。

公开(公告)号：US06871169B1

公开(公告)日：2005-03-22

申请号：US09630201

申请日：2000-08-01

申请人： Kevin H. Hazen ,  Suresh Thennadil ,  Timothy L. Ruchti

发明人： Kevin H. Hazen ,  Suresh Thennadil ,  Timothy L. Ruchti

IPC分类号： G01N21/27 ,  G01N21/35 ,  G06F7/60 ,  G06F17/10 ,  G06F101/00

CPC分类号： G01N21/359 ,  G01N21/274 ,  G01N21/3577

摘要： A novel multivariate model for analysis of absorbance spectra allows for each wavelength or spectral region to be modeled with just enough factors to fully model the analytical signal without the incorporation of noise by using excess factors. Each wavelength or spectral region is modeled utilizing its own number of factors independently of other wavelengths or spectral regions. An iterative combinative PCR algorithm allows a different number of factors to be applied to different wavelengths. In an exemplary embodiment, a three-factor model is applied over a given spectral region. The residual of the three-factor model is calculated and used as the input for an additional five-factor model. Prior to the additional five factors being applied, some of the wavelengths are removed. This leads to a three-factor model over the first region and an eight-factor model over the second region. This analysis of residuals can be repeated such that a one to n factor model could be applied to any given wavelength, or rather any number of factors may be employed to model any given frequency or spectral region. A method of predicting concentration of a target analyte from sample spectra applies a calibration developed using the inventive PCR algorithm to a matrix of sample spectral to generate a vector of predicted concentrations for the target analyte.

摘要翻译： 用于分析吸收光谱的新型多变量模型允许将每个波长或光谱区域用足够的因子进行建模，以完全建模分析信号，而不会通过使用过量因子来引入噪声。 每个波长或光谱区域都利用独立于其他波长或光谱区域的其自身数量的因子进行建模。 迭代组合PCR算法允许将不同数量的因子应用于不同波长。 在示例性实施例中，三因素模型被应用于给定的光谱区域。 计算三因素模型的残差，并将其用作额外的五因素模型的输入。 在应用额外的五个因素之前，一些波长被去除。 这导致了第一个区域的三因素模型和第二个区域的八因素模型。 可以重复残差的这种分析，使得可以对任何给定波长应用一到一因子模型，或者可以采用任何数量的因素来建模任何给定的频率或光谱区域。 从样品光谱预测目标分析物的浓度的方法将使用本发明的PCR算法开发的校准应用于样品光谱的矩阵，以产生靶分析物的预测浓度的载体。

公开(公告)号：US06512936B1

公开(公告)日：2003-01-28

申请号：US09665201

申请日：2000-09-18

申请人： Stephen L. Monfre ,  Thomas B. Blank ,  Timothy L. Ruchti ,  Suresh Thennadil

发明人： Stephen L. Monfre ,  Thomas B. Blank ,  Timothy L. Ruchti ,  Suresh Thennadil

IPC分类号： A61B500

CPC分类号： G06K9/6217 ,  A61B5/1075 ,  A61B5/14532 ,  A61B5/1455 ,  A61B5/1495 ,  A61B5/7264 ,  A61B2560/0223 ,  A61B2560/0233 ,  G01N21/274 ,  G01N21/359 ,  G01N21/4785 ,  G01N21/49 ,  Y10S128/92

摘要： A method of multi-tier classification and calibration in noninvasive blood analyte prediction minimizes prediction error by limiting co-varying spectral interferents. Tissue samples are categorized based on subject demographic and instrumental skin measurements, including in vivo near-IR spectral measurements. A multi-tier intelligent pattern classification sequence organizes spectral data into clusters having a high degree of internal consistency in tissue properties. In each tier, categories are successively refined using subject demographics, spectral measurement information and other device measurements suitable for developing tissue classifications. The multi-tier classification approach to calibration utilizes multivariate statistical arguments and multi-tiered classification using spectral features. Variables used in the multi-tiered classification can be skin surface hydration, skin surface temperature, tissue volume hydration, and an assessment of relative optical thickness of the dermis by the near-IR fat band. All tissue parameters are evaluated using the NIR spectrum signal along key wavelength segments.

摘要翻译： 非侵入性血液分析物预测中的多层分类和校准方法通过限制共同变化的光谱干扰来最小化预测误差。 组织样品根据受试者的人口统计学和仪器皮肤测量进行分类，包括体内近红外光谱测量。 多层智能图案分类序列将光谱数据组织成具有组织性质内部高度一致性的簇。 在每个层次中，使用主题人口统计学，光谱测量信息和适合于开发组织分类的其它装置测量法来连续地改进类别。 校准的多层分类方法利用多变量统计学参数和使用光谱特征的多层次分类。 用于多层分类的变量可以是皮肤表面水合，皮肤表面温度，组织体积水合，以及近红外脂肪带对真皮的相对光学厚度的评估。 使用沿关键波长段的NIR光谱信号评估所有组织参数。

公开(公告)号：US06512937B2

公开(公告)日：2003-01-28

申请号：US09825687

申请日：2001-04-03

申请人： Thomas B. Blank ,  Stephen L. Monfre ,  Timothy L. Ruchti ,  Suresh Thennadil

发明人： Thomas B. Blank ,  Stephen L. Monfre ,  Timothy L. Ruchti ,  Suresh Thennadil

IPC分类号： A61B500

CPC分类号： G01N21/274 ,  A61B5/1075 ,  A61B5/14532 ,  A61B5/1455 ,  A61B5/1495 ,  A61B5/7264 ,  A61B5/7267 ,  A61B2560/0223 ,  A61B2560/0233 ,  G01N21/359 ,  G01N21/4785 ,  G01N21/49 ,  Y10S128/92

摘要： A method of multi-tier classification and calibration in noninvasive blood analyte prediction minimizes prediction error by limiting co-varying spectral interferents. Tissue samples are categorized based on subject demographic and instrumental skin measurements, including in vivo near-IR spectral measurements. A multi-tier intelligent pattern classification sequence organizes spectral data into clusters having a high degree of internal consistency in tissue properties. In each tier, categories are successively refined using subject demographics, spectral measurement information and other device measurements suitable for developing tissue classifications. The multi-tier classification approach to calibration utilizes multivariate statistical arguments and multi-tiered classification using spectral features. Variables used in the multi-tiered classification can be skin surface hydration, skin surface temperature, tissue volume hydration, and an assessment of relative optical thickness of the dermis by the near-IR fat band. All tissue parameters are evaluated using the NIR spectrum signal along key wavelength segments.

摘要翻译： 非侵入性血液分析物预测中的多层分类和校准方法通过限制共同变化的光谱干扰来最小化预测误差。 组织样品根据受试者的人口统计学和仪器皮肤测量进行分类，包括体内近红外光谱测量。 多层智能图案分类序列将光谱数据组织成具有组织性质内部高度一致性的簇。 在每个层次中，使用主体人口统计学，光谱测量信息和适合于开发组织分类的其他设备测量来连续地改进类别。多层分类校准方法利用多变量统计学参数和使用光谱特征的多层次分类。 用于多层分类的变量可以是皮肤表面水合，皮肤表面温度，组织体积水合，以及近红外脂肪带对真皮的相对光学厚度的评估。 使用沿关键波长段的NIR光谱信号评估所有组织参数。

公开(公告)号：US20060167350A1

公开(公告)日：2006-07-27

申请号：US11065223

申请日：2005-02-23

申请人： Stephen Monfre ,  Thomas Blank ,  Timothy Ruchti ,  Suresh Thennadil

发明人： Stephen Monfre ,  Thomas Blank ,  Timothy Ruchti ,  Suresh Thennadil

IPC分类号： A61B5/00

CPC分类号： A61B5/1455 ,  A61B5/0059 ,  A61B5/14532 ,  A61B5/7264

摘要： A method of multi-tier classification and calibration in noninvasive blood analyte prediction is provided that minimizes prediction error by limiting co-varying spectral interferents. Tissue samples are categorized based on subject demographic and instrumental skin measurements, including in-vivo near-IR spectral measurements. A multi-tier intelligent pattern classification sequence organizes spectral data into clusters that have a high degree of internal consistency in tissue properties. In each tier, categories are successively refined using subject demographics, spectral measurement information, and other device measurements suitable for developing tissue classifications. The multi-tier classification approach to calibration uses multivariate statistical arguments and multi-tiered classification using spectral features. Variables used in the multi-tiered classification can be skin surface hydration, skin surface temperature, tissue volume hydration, and an assessment of relative optical thickness of the dermis by the near-IR fat band. All tissue parameters are evaluated using the NIR spectrum signal along key wavelength segments.

摘要翻译： 提供了一种在非侵入性血液分析物预测中进行多层次分类和校准的方法，通过限制共同变化的光谱干扰物来最小化预测误差。 组织样本根据受试者的人口统计学和仪器皮肤测量进行分类，包括体内近红外光谱测量。 多层智能图案分类序列将光谱数据组织成具有组织性质内部一致性高度的簇。 在每个层次中，使用主题人口统计学，光谱测量信息和适合于开发组织分类的其它装置测量法来连续地改进类别。 多级分类校准方法使用多变量统计学参数和使用光谱特征的多层次分类。 用于多层分类的变量可以是皮肤表面水合，皮肤表面温度，组织体积水合，以及近红外脂肪带对真皮的相对光学厚度的评估。 使用沿关键波长段的NIR光谱信号评估所有组织参数。