Systematic wavelength selection for improved multivariate spectral analysis
First Claim
1. In a method for use with optical instrumentation for determining one or more unknown values of at least one known characteristic by an optical measurement, said method including the steps of:
- (a) irradiating said material having said unknown values of said known characteristic with electromagnetic energy including at least several wavelengths so that there is differential absorption of at least some of said wavelengths by said material as a function of said wavelengths and said characteristic, said differential absorption causing intensity variations of said wavelengths incident from said material as a function of said wavelengths and said unknown values of said known characteristic;
(b) measuring said intensity variations from said material; and
(c) calculating said unknown values of said known characteristic in said material from said measured intensity variations utilizing an algorithm and a model, said algorithm being capable of using all independent sources of intensity variations v. wavelengths information obtained from irradiating a set of samples with a range of wavelengths in which said values of said known characteristic are known, said algorithm also being capable of using more wavelengths than samples in said set of samples, said model constructed from said set of samples and being a function of said known values of said characteristic and said intensity variations v. wavelengths information obtained from irradiating said set of samples, the improvement comprising selecting multiple variable subsets for generation and use in an improved model, each of said subsets containing one or more variables, said model being improved by selecting said multiple variable subsets from the set of instrument variables and wherein said algorithm with said improved model improves the fitness for said determination of said unknown values of said known characteristic, said selection process utilizing multivariate search methods that select both predictive and synergistic variables.
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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=ƒ(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.
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Citations
25 Claims
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1. In a method for use with optical instrumentation for determining one or more unknown values of at least one known characteristic by an optical measurement, said method including the steps of:
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(a) irradiating said material having said unknown values of said known characteristic with electromagnetic energy including at least several wavelengths so that there is differential absorption of at least some of said wavelengths by said material as a function of said wavelengths and said characteristic, said differential absorption causing intensity variations of said wavelengths incident from said material as a function of said wavelengths and said unknown values of said known characteristic; (b) measuring said intensity variations from said material; and (c) calculating said unknown values of said known characteristic in said material from said measured intensity variations utilizing an algorithm and a model, said algorithm being capable of using all independent sources of intensity variations v. wavelengths information obtained from irradiating a set of samples with a range of wavelengths in which said values of said known characteristic are known, said algorithm also being capable of using more wavelengths than samples in said set of samples, said model constructed from said set of samples and being a function of said known values of said characteristic and said intensity variations v. wavelengths information obtained from irradiating said set of samples, the improvement comprising selecting multiple variable subsets for generation and use in an improved model, each of said subsets containing one or more variables, said model being improved by selecting said multiple variable subsets from the set of instrument variables and wherein said algorithm with said improved model improves the fitness for said determination of said unknown values of said known characteristic, said selection process utilizing multivariate search methods that select both predictive and synergistic variables. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
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Specification