Systematic wavelength selection for improved multivariate spectral analysis

• US 5,857,462 A
• Filed: 07/24/1995
• Issued: 01/12/1999
• Est. Priority Date: 08/10/1993
• Status: Expired due to Fees

• Current Assignee: Sandia Corporation (Martin Marietta Corporation)
• Original Assignee: Sandia Corporation (Martin Marietta Corporation)
• Inventors: Haaland, David M., Thomas, Edward V., Robinson, Mark R.
• Primary Examiner(s): Bahr, Jennifer
• Assistant Examiner(s): YARNELL, BRYAN KEITH
• Application Number:
  US08/505,829
• Time in Patent Office: 1,268 Days
• Field of Search: 128/633, 128/664-7, 359/39-41
• US Class Current: 600/310
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/14552 Details of sensors specially adapted therefor
• CPC Class Codes: A61B 5/1464 specially adapted for foetal tissue
• CPC Class Codes: A61B 5/6826 Finger
• CPC Class Codes: A61B 5/6838 Clamps or clips
• CPC Class Codes: A61B 5/6843 Monitoring or controlling sensor contact pressure
• CPC Class Codes: G01N 21/31 Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry G01N21/72 takes precedence

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=f (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.

Claims

1. A method of determining non-invasively a concentration of a blood analyte in human tissue, said method including the steps of:

a. irradiating said human tissue having unknown blood analyte concentration with electromagnetic energy including at least several wavelengths so that there is differential absorption of at least some of said wavelengths by said irradiated tissue as a function of said wavelengths and said blood analyte concentration, said differential absorption causing intensity variations of said wavelengths incident from said irradiated tissue;

b. measuring the intensities of said wavelengths incident from said irradiated tissue;

c. calculating said blood analyte concentration in said irradiated tissue from said measured intensities utilizing an algorithm and a model, said algorithm being capable of utilizing more of said measured intensities than calibration samples in which said blood analyte concentration is known, said model using selected wavelength subsets, said wavelength subsets comprising one or more of said wavelengths, said wavelength subsets are not systematically spaced, but are irregularly defined regions of the spectrum being used for analysis.

2. The method as set forth in claim 1, wherein the selection of said set of wavelength subsets is made independent of the knowledge of the spectral features of said irradiated tissue.

3. The method as set forth in claim 1, wherein said wavelength subsets are selected from wavelengths of light in the visible and infrared wavelength region by a multivariate search method for their predictive and synergistic ability to model the relationship between spectral information and known values of said blood analyte.

4. The method as set forth in claim 3, wherein said wavelength subset selection process is made utilizing a genetic algorithm.

5. The method as set forth in claim 1, wherein said algorithm is selected from the group including PLS, PLS2, PCR, CLS, Q-matrix, cross-correlation, Kalman filtering, neural networks, and continuum regression.

6. The method as set forth in claim 1 wherein the blood analyte is selected from the group including glucose, alcohol, ketones, fatty acids, cholesterol, lipoproteins, triglycerides, white blood cells, hematocrit, hemoglobin, blood urea nitrogen, creatinine, bilirubin, and electrolytes.

7. Apparatus for determining non-invasively a concentration of a blood analyte in human tissue, said apparatus comprising:

a. means for irradiating said human tissue having unknown blood analyte concentration with electromagnetic energy including at least several wavelengths so that there is differential absorption of at least some of said wavelengths by said irradiated tissue as a function of said wavelengths and said blood analyte concentration, said differential absorption causing intensity variations of said wavelengths incident from said irradiated tissue;

b. means for measuring the intensities of said wavelengths from said irradiated tissue;

c. means for calculating said blood analyte concentration in said irradiated tissue from said measured intensities utilizing an algorithm and a model, said algorithm also being capable of utilizing more of said measured intensities than than calibration samples in which said blood analyte concentration is known, said model using selected wavelength subsets, said wavelength subsets comprising one or more of said wavelengths, said wavelength subsets are not systematically spaced, but are irregularly defined regions of the spectrum being used for analysis.