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    • 6. 再颁专利
    • 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
    • USRE41333E1
    • 2010-05-11
    • US11046673
    • 2005-01-27
    • Thomas B. BlankStephen L. MonfreTimothy L. RuchtiSuresh N. Thennadill
    • Thomas B. BlankStephen L. MonfreTimothy L. RuchtiSuresh N. Thennadill
    • A61B5/1455
    • G01N21/274A61B5/1075A61B5/14532A61B5/1455A61B5/1495A61B5/7264A61B2560/0223A61B2560/0233G01N21/359G01N21/4785G01N21/49
    • 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。 用于多层次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。
    • 7. 发明授权
    • Method of adapting in-vitro models to aid in noninvasive glucose determination
    • 适应体外模型以帮助非侵入性葡萄糖测定的方法
    • US07317938B2
    • 2008-01-08
    • US10978116
    • 2004-10-29
    • Alexander D. LorenzTimothy L. Ruchti
    • Alexander D. LorenzTimothy L. Ruchti
    • A61B5/00
    • A61B5/1455A61B5/14532A61B2560/0233G01N21/278G01N21/359
    • The invention relates to a noninvasive analyzer and a method of using information determined at least in part from in-vitro spectra of tissue phantoms or analyte solutions to aid in the development of a noninvasive glucose concentration analyzer and/or in the analysis of noninvasive spectra resulting in glucose concentration estimations in the body. The preferred apparatus is a spectrometer that includes a base module and a sample module that is semi-continuously in contact with a human subject and that collects spectral measurements which are used to determine a biological parameter in the sampled tissue, such as glucose concentration. Collection of in-vitro samples is, optionally, performed on a separate instrument from the production model allowing the measurement technology to be developed on a research grade instrument and used or transferred to a target product platform or production analyzer for noninvasive glucose concentration estimation.
    • 本发明涉及非侵入性分析仪和使用至少部分地从组织模型或分析物溶液的体外光谱确定的信息的方法,以帮助非侵入性葡萄糖浓度分析仪的开发和/或在非侵入性光谱的分析中得到 在体内的葡萄糖浓度估计。 优选的装置是一种光谱仪,其包括基本模块和与人类受试者半连续接触的样本模块,并收集用于确定采样组织中的生物学参数(如葡萄糖浓度)的光谱测量。 体外样品的收集可选地在与生产模型分开的仪器上进行,允许在研究级仪器上开发测量技术,并将其用于或转移到用于非侵入性葡萄糖浓度估计的目标产物平台或生产分析仪。