Systematic wavelength selection for improved multivariate spectral analysis
Abstract
Methods and apparatus for determining in a biological material one or more unknown values of at least one known characteristic (e.g. the concentration of an analyte such as glucose in blood or the concentration of one or more blood gas parameters) with a model based on a set of samples with known values of the known characteristics and a multivariate algorithm using several wavelength subsets. The method includes selecting multiple wavelength subsets, from the electromagnetic spectral region appropriate for determining the known characteristic, for use by an algorithm wherein the selection of wavelength subsets improves the model's fitness of the determination for the unknown values of the known characteristic. The selection process utilizes multivariate search methods that select both predictive and synergistic wavelengths within the range of wavelengths utilized. The fitness of the wavelength subsets is determined by the fitness function F=.function.(cost, performance). The method includes the steps of: (1) using one or more applications of a genetic algorithm to produce one or more count spectra, with multiple count spectra then combined to produce a combined count spectrum; (2) smoothing the count spectrum; (3) selecting a threshold count from a count spectrum to select these wavelength subsets which optimize themore »
 Inventors:

 2828 Georgia NE., Albuquerque, NM 87110
 1603 Solano NE., Albuquerque, NM 87110
 809 Richmond Dr. SE., Albuquerque, NM 87106
 Issue Date:
 Research Org.:
 Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA
 OSTI Identifier:
 869996
 Patent Number(s):
 5435309
 Assignee:
 Thomas, Edward V. (2828 Georgia NE., Albuquerque, NM 87110);Robinson, Mark R. (1603 Solano NE., Albuquerque, NM 87110);Haaland, David M. (809 Richmond Dr. SE., Albuquerque, NM 87106)
 DOE Contract Number:
 AC0476
 Resource Type:
 Patent
 Country of Publication:
 United States
 Language:
 English
 Subject:
 systematic; wavelength; selection; improved; multivariate; spectral; analysis; methods; apparatus; determining; biological; material; values; characteristic; concentration; analyte; glucose; blood; gas; parameters; model; based; set; samples; characteristics; algorithm; subsets; method; selecting; multiple; electromagnetic; region; appropriate; improves; fitness; determination; process; utilizes; select; predictive; synergistic; wavelengths; range; utilized; determined; function; cost; performance; steps; applications; genetic; produce; count; spectra; combined; spectrum; smoothing; threshold; optimize; eliminating; portion; selected; noninvasively; vivo; invasively; vitro; spectral analysis; process utilizes; selected wavelength; biological material; multivariate algorithm; spectral region; multiple wavelength; blood gas; selected wave; genetic algorithm; gas parameters; electromagnetic spectral; /600/250/356/
Citation Formats
Thomas, Edward V, Robinson, Mark R, and Haaland, David M. Systematic wavelength selection for improved multivariate spectral analysis. United States: N. p., 1995.
Web.
Thomas, Edward V, Robinson, Mark R, & Haaland, David M. Systematic wavelength selection for improved multivariate spectral analysis. United States.
Thomas, Edward V, Robinson, Mark R, and Haaland, David M. Sun .
"Systematic wavelength selection for improved multivariate spectral analysis". United States. https://www.osti.gov/servlets/purl/869996.
@article{osti_869996,
title = {Systematic wavelength selection for improved multivariate spectral analysis},
author = {Thomas, Edward V and Robinson, Mark R and Haaland, David M},
abstractNote = {Methods and apparatus for determining in a biological material one or more unknown values of at least one known characteristic (e.g. the concentration of an analyte such as glucose in blood or the concentration of one or more blood gas parameters) with a model based on a set of samples with known values of the known characteristics and a multivariate algorithm using several wavelength subsets. The method includes selecting multiple wavelength subsets, from the electromagnetic spectral region appropriate for determining the known characteristic, for use by an algorithm wherein the selection of wavelength subsets improves the model's fitness of the determination for the unknown values of the known characteristic. The selection process utilizes multivariate search methods that select both predictive and synergistic wavelengths within the range of wavelengths utilized. The fitness of the wavelength subsets is determined by the fitness function F=.function.(cost, performance). The method includes the steps of: (1) using one or more applications of a genetic algorithm to produce one or more count spectra, with multiple count spectra then combined to produce a combined count spectrum; (2) smoothing the count spectrum; (3) selecting a threshold count from a count spectrum to select these wavelength subsets which optimize the fitness function; and (4) eliminating a portion of the selected wavelength subsets. The determination of the unknown values can be made: (1) noninvasively and in vivo; (2) invasively and in vivo; or (3) in vitro.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1995},
month = {1}
}