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    • 6. 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
    • US06777240B2
    • 2004-08-17
    • US10241344
    • 2002-09-11
    • 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;'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).
    • 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。
    • 9. 发明授权
    • Multi-tier method of developing localized calibration models for non-invasive blood analyte prediction
    • 开发用于非侵入性血液分析物预测的局部校准模型的多层方法
    • US06512937B2
    • 2003-01-28
    • US09825687
    • 2001-04-03
    • Thomas B. BlankStephen L. MonfreTimothy L. RuchtiSuresh Thennadil
    • Thomas B. BlankStephen L. MonfreTimothy L. RuchtiSuresh Thennadil
    • A61B500
    • G01N21/274A61B5/1075A61B5/14532A61B5/1455A61B5/1495A61B5/7264A61B5/7267A61B2560/0223A61B2560/0233G01N21/359G01N21/4785G01N21/49Y10S128/92
    • 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.
    • 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。