Automatic process for sample selection during multivariate...

Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Chemical analysis

Reexamination Certificate

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Reexamination Certificate

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06876931

ABSTRACT:
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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patent: 6134458 (2000-10-01), Rosenthal
patent: 6135965 (2000-10-01), Tumer et al.
patent: 6280381 (2001-08-01), Malin et al.

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