发明名称 |
Automatic process for sample selection during multivariate calibration |
摘要 |
A process for enhancing a multivariate calibration through optimization of a calibration data set operates on a large calibration set of samples that includes measurements and associated reference values to automatically select an optimal sub-set of samples that enables calculation of an optimized calibration model. The process is automatic and bases sample selection on two basic criteria: enhancement of correlation between a partner variable extracted from the independent variable and the dependent variable and reduction of correlation between the dependent variable and interference. The method includes two fundamental steps: evaluation, assigning a measurement of calibration suitability to a subset of data; and optimization, selecting an optimal subset of data as directed by the measurement of suitability. The process is particularly applied in enhancing and automating the calibration process for non-invasive measurement glucose measurement but can be applied in any system involving the calculation of multivariate models from empirical data sets.
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申请公布号 |
US6876931(B2) |
申请公布日期 |
2005.04.05 |
申请号 |
US20020211142 |
申请日期 |
2002.08.02 |
申请人 |
SENSYS MEDICAL INC. |
发明人 |
LORENZ ALEXANDER D.;RUCHTI TIMOTHY L.;BLANK THOMAS B. |
分类号 |
A61B5/00;G01N21/27;G01N21/35;(IPC1-7):G01N31/00 |
主分类号 |
A61B5/00 |
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