Method and System for Non-Invasive Optical Blood Glucose Detection Utilizing Spectral Data Analysis

• US 20090292186A1
• Filed: 04/17/2009
• Published: 11/26/2009
• 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
• Granted Patent: US 8,340,738 B2
• Time in Patent Office: Days
• 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 detector positioned to receive light from the at least one light source and to generate an output signal, having a time dependent current, which is indicative of the power of light detected; and

a processor that receives the output signal from the at least one light detector and based on the received output signal, calculates the attenuance attributable to blood in a sample present in the target area with a signal-to-noise ratio of at least 20-to-1, and based on the calculated attenuance, determines 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 time dependent output current is a function of a baseline current, a noise current and a time dependent cyclic current corresponding to a heartbeat.

3. The system for detecting glucose in a biological sample according to claim 2, wherein the calculated attenuance is based at least in part on a standard deviation of a logarithm of the time dependent output current.

4. The system for detecting glucose in a biological sample according to claim 2, wherein the calculated attenuance is based at least in part on an approximation of a standard deviation of a logarithm of the time dependent output current.

5. The system for detecting glucose in a biological sample according to claim 1, further comprising a peak-to-valley height of the change in light absorption due to blood in the sample in relationship to time, which is calculated by the processor as a function of a standard deviation of a logarithm of the time dependent output current divided by a proportionality constant:

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

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

7. The system for detecting glucose in a biological sample according to claim 6, wherein the processor is configured to calculate the normalization factor Q_i(C,T) at a plurality of wavelengths, the ith wavelength being represented by λ

_i, based on the time dependent detector output signal

8. The system for detecting glucose in a biological sample according to claim 7, 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;

9. The system for detecting glucose in a biological sample according to claim 8, wherein values of the temperature dependent regression coefficient a_i(T) can be extracted using partial least squares regression with the processor.

10. The system for detecting glucose in a biological sample according to claim 7, 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;

11. The system for detecting glucose in a biological sample according to claim 10, wherein values of the sample temperature independent regression coefficient b_i and the regression coefficient for sample temperature η

can be extracted using partial least squares regression with the processor.

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

a processor that receives the output signal from the at least one light detector and based on the received output signal, calculates the attenuance attributable to blood in a sample present in the target area with a ratio factor, and based on the calculated attenuance, determines a blood glucose level associated with a sample present in the target area.

13. The system for detecting glucose in a biological sample according to claim 12, wherein the processor is configured to calculate the ratio factor Y_ij(C,T) at a plurality of wavelengths, the ith wavelength being represented by λ

_i,the j^th wavelength being represented by λ

_j, C is a blood glucose concentration, T is temperature of the biological sample, I_D(λ

_i,t) is the time dependent output current, σ

[log I_D(λ

_i,t)] is standard deviation of the logarithm of the time dependent output current, and t is time, according to the equation;

14. The system for detecting glucose in a biological sample according to claim 13, wherein the processor is configured to calculate the blood glucose level C_optical based on the optical measurement, Y_ij(C,T) and f_i(T), which is the temperature dependent regression coefficient corresponding to wavelength λ

_i according to the equation;

15. The system for detecting glucose in a biological sample according to claim 14, wherein values of the temperature dependent regression coefficient corresponding to wavelength λ

_i, which is f_i(T), can be extracted using partial least squares regression with the processor.

16. The system for detecting glucose in a biological sample according to claim 13, wherein the processor is configured to calculate the blood glucose level C_optical based on a temperature independent regression coefficient h_i, a regression coefficient β

for the temperature of the biological sample T, the ratio factor Y_ij(C,T) for a number of wavelengths N according to the equation;

17. The system for detecting glucose in a biological sample according to claim 16, wherein values of the temperature independent regression coefficient h_i and the regression coefficient β

for the temperature of the biological sample T can be extracted using partial least squares regression with the processor.

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

a processor that receives the output signal from the at least one light detector and based on the received output signal, calculates the attenuance attributable to blood in a sample present in the target area and eliminates effect of uncertainty caused by temperature dependent detector response of the at least one light detector, and based on the calculated attenuance, determines a blood glucose level associated with a sample present in the target area.

19. The system for detecting glucose in a biological sample according to claim 18, wherein elimination of effect of uncertainty caused by temperature of the at least one light detector is accomplished by calculating the standard deviation of the logarithm of the time dependent current with the processor.

20. The system for detecting glucose in a biological sample according to claim 19, wherein elimination of effect of uncertainty caused by temperature of the at least one light detector is accomplished by calculating the following equation with the processor:

σ

[log I_D(λ

_i,t)]=σ

[log P(λ

_i,t)], where the i^th wavelength being represented by λ

_i, based on the time dependent detector output current signal I_D(λ

_i,t) and the time dependent detector power signal P(λ

_i,t), where log I_D(λ

_i,t) is the logarithm of the time dependent detector output current signal and log P(λ

_i,t) is the logarithm of the time dependent light power received by the corresponding detector.

21. The system for detecting glucose in a biological sample according to claim 18, wherein the at least one light detector includes a preamplifier having a feedback resistor.

22. 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 detector, which includes a preamplifier having a feedback resistor, positioned to receive light from the at least one light source and to generate an output signal, having a time dependent current, which is indicative of the power of light detected; and

a processor that receives the output signal from the at least one light detector and based on the received output signal, calculates the attenuance attributable to blood in a sample present in the target area and eliminates effect of uncertainty caused by temperature dependent detector response of the at least one light detector, and based on the calculated attenuance, determines a blood glucose level associated with a sample present in the target area.

23. The system for detecting glucose in a biological sample according to claim 22, wherein elimination of effect of uncertainty caused by temperature of the at least one light detector, which includes a preamplifier having a feedback resistor, is accomplished by calculating the standard deviation of the logarithm of the time dependent voltage signal with the processor.

24. The system for detecting glucose in a biological sample according to claim 22, wherein the processor is configured to calculate a normalization factor Q_i(C,T) based on the preamplifier output voltage V_i(t) as a function of time and standard deviation σ

according to the equation;

25. The system for detecting glucose in a biological sample according to claim 22, wherein the processor is configured to calculate a ratio factor Y_ij(C,T) based on the preamplifier output voltage V_i(t) as a function of time and standard deviation σ

according to the equation;

26. The system for detecting glucose in a biological sample according to claim 22, further comprising an analog-to-digital convertor having a digitized voltage output.

27. The system for detecting glucose in a biological sample according to claim 26, wherein the processor is configured to calculate a normalization factor Q_i(C,T) based on the analog-to-digital convertor voltage output Δ

(ADC)_i, where σ

is standard deviation according to the equation;

28. The system for detecting glucose in a biological sample according to claim 26, wherein the processor is configured to calculate a ratio factor Y_ij(C,T) based on the analog-to-digital convertor voltage output Δ

(ADC)_i, where σ

is standard deviation according to the equation;

29. 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 detector positioned to receive light from the at least one light source 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 signal-to-noise ratio of at least 20-to-1; and

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

30. The method for detecting glucose in a biological sample according to claim 29, wherein the step of calculating the attenuance attributable to blood in a sample present in the target area is based at least in part on a standard deviation of a logarithm of the time dependent output current.

31. The method for detecting glucose in a biological sample according to claim 29, further comprising calculating a peak-to-valley height of the change in light absorption due to blood in the sample in relationship to time with the processor, which is a function of a standard deviation of a logarithm of the time dependent output current divided by a proportionality constant:

32. 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 detector positioned to receive light from the at least one light source 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.

33. The method for detecting glucose in a biological sample according to claim 32, 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

34. The method for detecting glucose in a biological sample of claim 33, 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;

35. The method for detecting glucose in a biological sample of claim 34, further comprising extracting values of the temperature dependent regression coefficient a_i(T) utilizing partial least squares regression with the processor.

36. The method for detecting glucose in a biological sample of claim 33, 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;

37. The method for detecting glucose in a biological sample of claim 36, 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.

38. 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 detector positioned to receive light from the at least one light source 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;

calculating the attenuance attributable to blood in a sample present in the target area with a ratio factor based on the received output signal 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.

39. The method for detecting glucose in a biological sample according to claim 38, further comprising calculating the ratio factor Y_ij(C,T) at a plurality of wavelengths with the processor, where the ith wavelength being represented by λ

_i,the j^th wavelength being represented by λ

_j, C is a blood glucose concentration, T is temperature of the biological sample, I_D(λ

_i,t) is the time dependent output current, σ

[log I_D(λ

_i,t)] is standard deviation of the logarithm of the time dependent output current, and t is time, according to the equation;

40. The method for detecting glucose in a biological sample according to claim 39, further comprising calculating the blood glucose level C_optical with the processor based on the optical measurement, Y_ij(C,T) and f_i(T), which is the temperature dependent regression coefficient corresponding to wavelength λ

_i according to the equation;

41. The method for detecting glucose in a biological sample according to claim 40, further comprising extracting the values f_i(T) of the temperature dependent regression coefficient corresponding to wavelength λ

_i utilizing partial least squares regression with the processor.

42. The method for detecting glucose in a biological sample according to claim 39, further comprising calculating blood glucose level C_optical with the processor based on a temperature-independent regression coefficient h_i, a regression coefficient β

for the temperature of the biological sample T, and the ratio factor Y_ij(C,T) for a number of wavelengths N according to the equation;

43. The method for detecting glucose in a biological sample according to claim 42, further comprising extracting values of the temperature-independent regression coefficient h_i and the regression coefficient β

for the temperature of the biological sample T utilizing partial least squares regression with the processor.

44. 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 detector positioned to receive light from the at least one light source 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 ratio factor with the processor;

eliminating effect of uncertainty caused by temperature dependent detector response of the at least one light detector with the processor; and

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

45. The method for detecting glucose in a biological sample according to claim 44, wherein the eliminating effect of uncertainty caused by temperature dependent detector response of the at least one light detector with the processor further includes calculating the standard deviation of the logarithm of the time dependent current with the processor.

46. The method for detecting glucose in a biological sample according to claim 44, wherein the at least one light detector includes a preamplifier having a feedback resistor.

47. The method for detecting glucose in a biological sample according to claim 46, further includes calculating at least one of a normalization factor Q_i(C,T) based on the preamplifier output voltage V_i(t) as a function of time and standard deviation σ

according to the equation;

48. The method for detecting glucose in a biological sample according to claim 46, further comprising utilizing an analog-to-digital convertor having a digitized voltage output.

49. The method for detecting glucose in a biological sample according to claim 48, further includes calculating at least one of a normalization factor Q_i(C,T) based on the analog-to-digital convertor voltage output Δ

(ADC)_i, where σ

is standard deviation according to the equation;