公开(公告)号：US06697654B2

公开(公告)日：2004-02-24

申请号：US10183906

申请日：2002-06-25

申请人： Alexander D. Lorenz ,  Thomas B. Blank ,  Timothy L. Ruchti

发明人： Alexander D. Lorenz ,  Thomas B. Blank ,  Timothy L. Ruchti

IPC分类号： A61B500

CPC分类号： G01N21/4785 ,  A61B5/1075 ,  A61B5/14532 ,  A61B5/1455 ,  A61B5/1495 ,  A61B5/7264

摘要： 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.

摘要翻译： 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。