Method of adapting in-vitro models to aid in noninvasive glucose determination

A computer implemented method for noninvasive estimation of a sample constituent property, comprising the steps of:

• providing a noninvasive signal;
• providing a first model, wherein said first model comprises coefficients that are generated at least in part with an in-vitro data set, wherein said in-vitro data set comprises a spectrum of a tissue phantom having at least one optical parameter representative of said noninvasive signal in terms of photonic scattering and/or absorbance;
• standardizing an in-vivo instrument system to said first model, wherein a second model is generated;
• and
• estimating and providing for use said sample property by applying said second model to said noninvasive signal.

An apparatus for noninvasive estimation of a sample constituent property from a noninvasive spectrum, comprising:

• an analyzer comprising a base module, a sample module, and a model residing in said analyzer;
• wherein said model comprises coefficients generated by standardizing an in-vivo system to an in-vitro data set,
• wherein said in-vitro data set comprises a spectrum of a tissue phantom having at least one optical parameter representative of said noninvasive spectrum in terms of photonic scattering and/or absorbance;
• and
• wherein said model is applied to said noninvasive spectrum for estimation of said sample constituent property.

A computer implemented method for noninvasive estimation of a sample constituent property, comprising the steps of:

• providing a first model, wherein said first model comprises coefficients that are generated at least in part with an in-vitro data set;
• standardizing an in-vivo instrument system to said first model to generate a second model, wherein said second model comprises a second set of coefficients;
• providing an in-vivo test set, comprising:
• at least one in-vivo test signal;
• and
• a reference sample concentration that is correlated with said in-vivo test signal;
• applying said second model to said in-vivo test set to generate a test value;
• providing an in-vivo measurement signal;
• and
• estimating and providing for use said sample constituent property using said second model and said in-vivo measurement signal, wherein said step of estimating comprises multiplication of said in-vivo measurement signal by both a regression vector and a scaling factor resulting in a product that is adjusted with an offset.

A computer implemented method for noninvasively estimating an analyte concentration, comprising the steps of:

• providing a first calibration model;
• removing at least one interference from said first model to form a second model, wherein said first model comprises coefficients derived from data comprised of at least twenty percent in-vitro data, wherein said step of removing comprises projecting said coefficients onto a null space of said interference;
• providing an in-vivo signal;
• and
• estimating and providing for use said analyte concentration using said second model and said in-vivo signal.

An apparatus for noninvasive estimation of a sample constituent property from a noninvasive spectrum, comprising:

• an analyzer, comprising:
• a base module;
• a sample module;
• and
• a model residing in said analyzer;
• wherein said model comprises coefficients generated by standardizing an in-vivo system to a model of coefficients derived at least in part from an in-vitro data set;
• wherein said in-vitro signal comprises a spectrum of a tissue phantom having at least one optical parameter representative of said noninvasive spectrum in terms of photonic scattering and/or absorbance;
• and
• wherein said model is applied to said noninvasive spectrum to generate said sample constituent property.

A computer implemented method for noninvasively estimating a blood/tissue glucose concentration, comprising the steps of:

• providing a noninvasive near-infrared signal;
• providing a calibration model;
• supplementing said calibration model with an in-vitro signal, wherein said in-vitro signal comprises a spectrum of a tissue phantom having at least one optical parameter representative of said noninvasive near-infrared signal in terms of photonic scattering and/or absorbance;
• and
• estimating and providing for use said blood glucose concentration using said model and said noninvasive signal.

A computer implemented method for noninvasive estimation of a sample constituent property from an in-vivo instrument system, comprising the steps of:

• providing a noninvasive signal;
• providing a model, comprising coefficients generated at least in part with an in-vitro data set, wherein said in-vitro data set comprises a spectrum of a tissue phantom having at least one optical parameter representative of said noninvasive spectrum in terms of photonic scattering and/or absorbance;
• standardizing said model to said in-vivo instrument system;
• and
• estimating and providing for use said sample property by applying said model to said noninvasive signal.