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    • 3. 发明申请
    • Method and apparatus for enhanced estimation of an analyte property through multiple region transformation
    • 用于通过多区域变换增强对分析物特性的估计的方法和装置
    • US20050149300A1
    • 2005-07-07
    • US10976530
    • 2004-10-29
    • Timothy RuchtiAlexander LorenzKevin Hazen
    • Timothy RuchtiAlexander LorenzKevin Hazen
    • A61B5/00G01N21/35G06F17/10
    • A61B5/1455A61B5/14532A61B5/1495A61B2560/0223G01N21/359
    • The invention provides for transformation of a section of a data block independently of the transformation of separate or overlapping data blocks to determine a property related to the original matrix, where each of the separate or overlapping data blocks are derived from an original data matrix. The transformation enhances parameters of a first data block over a given region of an axis of the data matrix, such as signal-to-noise, without affecting analysis of a second data block derived from the data matrix. This allows for enhancement of analysis of an analyte property, such as concentration, represented within the original data matrix. In a first embodiment of the invention, a separate decomposition and factor selection for each selected data matrix is performed with subsequent score matrix concatenization. The combined score matrix is used to generate a model that is subsequently used to estimate a property, such as concentration represented in the original data matrix. In a second embodiment, each data matrix is independently preprocessed. Demonstration of the invention is performed through glucose concentration estimation from noninvasive spectra of the body.
    • 本发明提供了数据块的一部分的变换,独立于单独或重叠的数据块的变换,以确定与原始矩阵相关的属性,其中分离的或重叠的数据块中的每一个从原始数据矩阵导出。 该变换增强了数据矩阵的轴的给定区域(例如信号到噪声)上的第一数据块的参数,而不影响从数据矩阵导出的第二数据块的分析。 这允许增强在原始数据矩阵内表示的分析物质(例如浓度)的分析。 在本发明的第一实施例中,对于每个选择的数据矩阵进行单独的分解和因子选择,随后的得分矩阵连接。 组合得分矩阵用于生成随后用于估计属性的模型,例如在原始数据矩阵中表示的浓度。 在第二实施例中,每个数据矩阵是独立预处理的。 本发明的演示通过来自身体的非侵入性光谱的葡萄糖浓度估计来进行。