Method and system for non-invasive optical blood glucose detection utilizing spectral data analysis

• US 8,340,738 B2
• Filed: 04/17/2009
• Issued: 12/25/2012
• Est. Priority Date: 05/22/2008
• Status: Active Grant

• Current Assignee: St. Louis Medical Devices, Inc.
• Original Assignee: Curators of the University of Missouri (University of Missouri)
• Inventors: Xu, Zhi
• Primary Examiner(s): SZMAL, BRIAN SCOTT
• Application Number:
  US12/425,535
• Publication Number:
  US 20090292186A1
• Time in Patent Office: 1,348 Days
• Field of Search: 600/309, 600/310, 600/316, 600/322, 600/323, 600/335, 600/336
• US Class Current: 600/316
• CPC Class Codes: A61B 2562/0238 Optical sensor arrangements for performing transmission measurements on body tissue
• CPC Class Codes: A61B 2576/00 Medical imaging apparatus involving image processing or analysis A61B1/00009, A61B6/52 and A61B8/52 take precedence; image processing per se G06T; details of algorithms for analysing medical images G06T7/0012
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/6826 Finger
• CPC Class Codes: A61B 5/6838 Clamps or clips
• CPC Class Codes: A61B 5/7225 Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

Systems and methods are disclosed for non-invasively measuring blood glucose levels in a biological sample based on spectral data. A variety of techniques are disclosed for improving signal-to-noise ratio in the acquisition of spectral data and calculating attenuance of light attributable to blood in a sample. Disclosed techniques include (1) using a standard deviation operation in conjunction with the logarithm function, (2) using a normalization factor, (3) using a ratio factor, (4) accounting for the effect of temperature on various system components such as resistors, and (5) accounting for dark current in a light detector by performing a calibration.

Claims

1. A system for detecting glucose in a biological sample, comprising:

at least one light source configured to strike a target area of a sample;

at least one light filter positioned to receive light transmitted through the target area of the sample from the at least one light source;

at least one light detector positioned to receive light from the at least one light source and filtered by the at least one light filter, and to generate an output signal, having a time dependent current, which is indicative of the power of light detected; and

a processor configured to receive the output signal from the at least one light detector and based on the received output signal, calculate the attenuance attributable to blood in a sample present in the target area with a normalization factor, and based on the calculated attenuance, determine a blood glucose level associated with a sample present in the target area.

2. The system for detecting glucose in a biological sample according to claim 1, wherein the processor is configured to calculate the normalization factor Q_i(C,T) at a plurality of wavelengths, the i^th wavelength being represented by λ

_i, based on the time dependent detector output signal

3. The system for detecting glucose in a biological sample according to claim 2, wherein the processor is configured to calculate the blood glucose level C_optical, where Q_i(C,T) is the normalization factor, a_i(T) is the temperature dependent regression coefficient corresponding to wavelength λ

_i, and N is number of wavelengths employed, according to the equation;

4. The system for detecting glucose in a biological sample according to claim 3, wherein the processor is configured to extract values of the temperature dependent regression coefficient a_i(T) using partial least squares regression with the processor.

5. The system for detecting glucose in a biological sample according to claim 2, wherein the processor is configured to calculate the blood glucose level C_optical based on the temperature independent regression coefficient, where Q_i(C,T) is the normalization factor, b_i is a sample temperature independent regression coefficient, η

is a regression coefficient for sample temperature, C is a blood glucose concentration, T is temperature of the biological sample, and N is number of wavelengths employed, according to the equation;

6. The system for detecting glucose in a biological sample according to claim 5, wherein the processor is configured to extract values of the sample temperature independent regression coefficient b_i and the regression coefficient for sample temperature η

using partial least squares regression with the processor.

7. A method for detecting glucose in a biological sample, comprising:

utilizing at least one light source configured to strike a target area of a sample;

utilizing at least one light filter positioned to receive light transmitted through the target area of the sample from the at least one light source;

utilizing at least one light detector positioned to receive light from the at least one light source and filtered by the at least one light filter, and to generate an output signal, having a time dependent, current, which is indicative of the power of light detected;

receiving the output signal from the at least one light detector with a processor and based on the received output signal;

calculating the attenuance attributable to blood in a sample present in the target area with a normalization factor with the processor; and

determining a blood glucose level associated with a sample present in the target area based on the calculated attenuance with the processor.

8. The method for detecting glucose in a biological sample according to claim 7, further comprising calculating the normalization factor Q_i(C,T) at a plurality of wavelengths with the processor, the i^th wavelength being represented by λ

_i, based on the time dependent detector output signal

9. The method for detecting glucose in a biological sample of claim 8, further comprising calculating the blood glucose level C_optical with the processor, where Q_i(C,T) is the normalization factor, a_i(T) is the temperature dependent regression coefficient corresponding to wavelength λ

_i, and N is number of wavelengths employed, according to the equation;

10. The method for detecting glucose in a biological sample of claim 9, further comprising extracting values of the temperature dependent regression coefficient a_i(T) utilizing partial least squares regression with the processor.

11. The method for detecting glucose in a biological sample of claim 8, further comprising calculating the blood glucose level C_optical with the processor based on the temperature independent regression coefficient, where Q_i(C,T) is the normalization factor, b_i is a sample temperature independent regression coefficient, η

is a regression coefficient for sample temperature, C is a blood glucose concentration, T is temperature of the biological sample, and N is number of wavelengths employed, according to the equation;

12. The method for detecting glucose in a biological sample of claim 11, further comprising extracting values of the sample temperature independent regression coefficient b_i and the regression coefficient for sample temperature η

utilizing partial least squares regression with the processor.