Sensys Medical, Inc.

Instrumentation Metrics, Inc.

Suresh Thennadil

Timothy Lewis Ruchti

Thomas B Blank

Stephen F Malin

Kevin H Hazen

Stephen L Monfre

Alexander D Lorenz

Jessica Rennert

Tamara L Troy

James Matthew Welch

Glenn Aaron Kees

A novel multivariate model for analysis of absorbance spectra allows for each wavelength or spectral region to be modeled with just enough factors to fully model the analytical signal without the incorporation of noise by using excess factors. Each wavelength or spectral region is modeled utilizing its own number of factors independently of other wavelengths or spectral regions. An iterative combinative PCR algorithm allows a different number of factors to be applied to different wavelengths. In an exemplary embodiment, a three-factor model is applied over a given spectral region. The residual of the three-factor model is calculated and used as the input for an additional five-factor model. Prior to the additional five factors being applied, some of the wavelengths are removed. This leads to a three-factor model over the first region and an eight-factor model over the second region. This analysis of residuals can be repeated such that a one to n factor model could be applied to any given wavelength, or rather any number of factors may be employed to model any given frequency or spectral region. A method of predicting concentration of a target analyte from sample spectra applies a calibration developed using the inventive PCR algorithm to a matrix of sample spectral to generate a vector of predicted concentrations for the target analyte.

Combinative multivariate calibration that enhances prediction ability through removal of over-modeled regions

The invention provides a class of samples that model the human body. This family of samples is based upon emulsions of oil in water with lecithin acting as the emulsifier. These solutions that have varying particle sizes may be spiked with basis set components (albumin, urea and glucose) to simulate skin tissues further. The family of samples is such that other organic compounds such as collagen, elastin, globulin and bilirubin may be added, as can salts such as Na , K and Cl . Layers of varying thickness with known index of refraction and particle size distributions may be generated using simple crosslinking reagents, such as collagen (gelatin). The resulting samples are flexible in each analyte's concentration and match the skin layers of the body in terms of the samples reduced scattering and absorption coefficients, &mgr;' and &mgr; . This family of samples is provided for use in the medical field where lasers and spectroscopy based analyzers are used in treatment of the body. In particular, knowledge may be gained on net analyte signal, photon depth of penetration, photon radial diffusion, photon interaction between tissue layers, photon density (all as a function of frequency) and on instrument parameter specifications such as resolution and required dynamic range (A/D bits required). In particular, applications to delineate such parameters have been developed for the application of noninvasive glucose determination in the near-IR region from 700 to 2500 nm with an emphasis on the region 1000 to 2500 nm (10,000 to 4,000 cm ).

Intra-serum and intra-gel for modeling human skin tissue

A method of multi-tier classification and calibration in noninvasive blood analyte prediction minimizes prediction error by limiting co-varying spectral interferents. Tissue samples are categorized based on subject demographic and instrumental skin measurements, including in vivo near-IR spectral measurements. A multi-tier intelligent pattern classification sequence organizes spectral data into clusters having a high degree of internal consistency in tissue properties. In each tier, categories are successively refined using subject demographics, spectral measurement information and other device measurements suitable for developing tissue classifications. The multi-tier classification approach to calibration utilizes multivariate statistical arguments and multi-tiered classification using spectral features. Variables used in the multi-tiered classification can be skin surface hydration, skin surface temperature, tissue volume hydration, and an assessment of relative optical thickness of the dermis by the near-IR fat band. All tissue parameters are evaluated using the NIR spectrum signal along key wavelength segments.

Multi-tier method of classifying sample spectra for non-invasive blood analyte prediction

Multi-tier method of developing localized calibration models for non-invasive blood analyte prediction

Noninvasive instrumentation and procedures have been developed for estimating the apparent age of human and animal subjects based on the irradiation of skin tissue with near-infrared light. The method of age estimation provides additional information about primary sources of systematic tissue variability due to chronological factors and environmental exposure. Therefore, categorization of subjects on the basis of the estimated apparent age is suitable for further spectral analysis and the measurement of biological and chemical compounds, such as blood analytes. Furthermore, age determination of subjects has particular benefit in assessment of therapies used to reduce the effects of ageing in tissue and measurement of tissue damage.

System for the noninvasive estimation of relative age

Instrumentation and procedures for noninvasively determining the sex of human and animal subjects in vivo have been developed based on the irradiation of skin tissue with near infrared light. The method of sex determination provides additional information about primary sources of systematic tissue variability, namely, the thickness of the dermis and the subcutaneous fat. Categorization of subjects on the basis of the determination is therefore suitable for further spectral analysis and the measurement of biological and chemical compounds, such as blood analytes.

Classification system for sex determination and tissue characterization

The invention provides a class of samples that model the human body. This family of samples is based upon emulsions of oil in water with lecithin acting as the emulsifier. These solutions that have varying particle sizes may be spiked with basis set components (albumin, urea and glucose) to simulate skin tissues further. The family of samples is such that other organic compounds such as collagen, elastin, globulin and bilirubin may be added, as can salts such as Na , K and Cl . Layers of varying thickness with known index of refraction and particle size distributions may be generated using simple crosslinking reagents, such as collagen (gelatin). The resulting samples are flexible in each analyte's concentration and match the skin layers of the body in terms of the samples reduced scattering and absorption coefficients, &mgr;m and &mgr;m . This family of samples is provided for use in the medical field where lasers and spectroscopy based analyzers are used in treatment of the body. In particular, knowledge may be gained on net analyte signal, photon depth of penetration, photon radial diffusion, photon interaction between tissue layers, photon density (all as a function of frequency) and on instrument parameter specifications such as resolution and required dynamic range (A/D bits required). In particular, applications to delineate such parameters have been developed for the application of noninvasive glucose determination in the near-IR region from 700 to 2500 nm with an emphasis on the region 1000 to 2500 nm (10,000 to 4,000 cm&minus; ).

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Tempe, AZ, United States of America

Suresh Thennadil