Low-cost method and apparatus for non-invasively measuring blood glucose levels

• US 6,968,221 B2
• Filed: 03/14/2003
• Issued: 11/22/2005
• Est. Priority Date: 03/14/2003
• Status: Expired due to Fees

• Current Assignee: Futrex, Inc.
• Original Assignee: Futrex, Inc.
• Inventors: Rosenthal, Robert D.
• Primary Examiner(s): WINAKUR, ERIC FRANK
• Application Number:
  US10/387,845
• Publication Number:
  US 20040181132A1
• Time in Patent Office: 984 Days
• Field of Search: 600/310, 600/322, 600/323, 600/316
• US Class Current: 600/316
• 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 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots

Abstract

A method and apparatus for measuring a blood analyte concentration using an inexpensive, low precision sensor device is provided. One embodiment of the method includes obtaining energy absorption measurement data through a body part of an individual. A plurality of indicator variables are subsequently calculated from the energy absorption measurement data. An indicator variable from the plurality of indicator variables having the highest correlation to blood glucose level is determined, and a first optical term based on the indicator variable with the highest correlation to blood glucose level is allocated to form a regression analysis equation. An estimated value of the blood analyte concentration using the regression analysis equation is calculated.

Claims

1. A method for measuring a blood analyte concentration, comprising the steps of:

obtaining energy absorption measurement data through a body part of an individual;

calculating a plurality of indicator variables associated with a cyclic pulse signal from said energy absorption measurement data;

determining which indicator variable from said plurality of indicator variables has the highest correlation to blood glucose level;

allocating a first optical term based on said indicator variable with said highest correlation to blood glucose level to form a regression analysis equation; and

calculating an estimated value of said blood analyte concentration using said regression analysis equation.

2. The method of claim 1, wherein said energy absorption measurement data is near-infrared energy absorption data and red light energy absorption data.

3. The method of claim 1, wherein said body part of said individual is a finger.

4. The method of claim 1, wherein said plurality of indicator variables are selected from the group consisting of pulse rate, LED pulse strength, IRED pulse strength, LED normalized pulse strength, IRED normalized pulse strength, pulse strength ratio, normalized pulse strength ratio, Delta OD, Delta OD divided by average LED Log 1/T, Delta OD divided by average IRED Log 1/T, Delta OD divided by average LED Log 1/T and average IRED Log 1/T, meal data, and occluded measurement data.

5. The method of claim 1, wherein said blood analyte concentration is a blood glucose concentration.

6. The method of claim 1, further comprising the step of calculating residual errors of said first optical term.

7. The method of claim 6, further comprising the steps of:

determining for each remaining indicator variable from said plurality of indicator variables which has the highest correlation to said residual errors;

allocating a second optical term based on said indicator variable with the highest correlation to said residual errors; and

adding said second optical term to said regression analysis equation.

8. The method of claim 1, wherein said regression analysis equation is a linear residual regression equation.

9. The method of claim 1, wherein said regression analysis equation is a linear regression equation.

10. The method of claim 1, wherein said regression analysis equation is a multiple linear regression equation.

11. A non-invasive measurement instrument for measuring a blood analyte concentration, comprising:

a first light source for introducing near-infrared energy into blood present in a body part of an individual;

a second light source for introducing red light energy into said blood present in said body part;

a detector for detecting said energy emerging from said body part, said detector producing an electrical signal indicative of said energy emerging from said body part; and

a processor for calculating a plurality of indicator variables associated with a cyclic pulse signal from said electrical signal, determining which indicator variable from said plurality of indicator variables has the highest correlation to blood glucose level, and calculating an estimated value of said blood analyte concentration based on said indicator variable having said highest correlation to blood glucose level,

wherein said blood analyte concentration is calculated using a regression analysis equation.

12. The measurement instrument of claim 11, wherein said plurality of indicator variables are selected from the group consisting of pulse rate, LED pulse strength, IRED pulse strength, LED normalized pulse strength, IRED normalized pulse strength, pulse strength ratio, normalized pulse strength ratio, Delta OD, Delta OD divided by average LED Log 1/T, Delta OD divided by average IRED Log 1/T, Delta OD divided by average LED Log 1/T and average IRED Log 1/T, meal data, and occluded measurement data.

13. The measurement instrument of claim 11, wherein said blood analyte concentration is a blood glucose concentration.

14. The measurement instrument of claim 11, further comprising a storage unit for storing said electrical signal, said plurality of indicator variables, and said regression analysis equation.

15. The measurement instrument of claim 11, wherein said processor calculates residual errors of said indicator variable having said highest correlation to blood glucose level.

16. The measurement instrument of claim 15, wherein a storage unit stores said residual errors.

17. The measurement instrument of claim 15, wherein said processor determines for each remaining indicator variable from said plurality of indicator variables which has the highest correlation to said residual errors, and calculates an estimated value of said blood analyte concentration based on said indicator variable having said highest correlation to said blood glucose level and said indicator variable having said highest correlation to said residual errors.

18. The measurement instrument of claim 11, further comprising an input device for entering meal data.

19. The measurement instrument of claim 11, further comprising a finger tourniquet for measuring occluded data.

20. The measurement instrument of claim 11, further comprising a display unit for displaying said estimated value of said blood analyte concentration.

21. The measurement instrument of claim 20, further comprising a warning device for notifying said individual of dangerous blood glucose levels.

22. The measurement instrument of claim 21, wherein the notification is at least one of a visual and audio indication.

23. The measurement instrument of claim 21, wherein said display unit and said warning device are in a second device.

24. The measurement instrument of claim 11, wherein said first light source, said second light source and said detector are in a first device, and said processor is in a second device connected to said first device through an electrical connection.

25. The measurement instrument of claim 11, wherein said body part of said individual is a finger.

26. The measurement instrument of claim 11, wherein said regression analysis equation is a linear residual regression equation.

27. The measurement instrument of claim 11, wherein said regression analysis equation is a linear regression equation.

28. The measurement instrument of claim 11, wherein said regression analysis equation is a multiple linear regression equation.

29. A method for measuring a blood analyte concentration, comprising the steps of:

obtaining red and near-infrared energy absorption measurement data through a body part of an individual;

calculating an indicator variable from said energy absorption measurement data;

allocating a first optical term based on said indicator variable to form a regression analysis equation; and

calculating an estimated value of said blood analyte concentration using said regression analysis equation,

wherein said indicator variable is at least one of a pulse rate, LED pulse strength, IRED pulse strength, LED normalized pulse strength, IRED normalized pulse strength, pulse strength ratio, normalized pulse strength ratio, Delta OD, Delta OD divided by average LED Log 1/T, Delta OD divided by average IRED Log 1/T, Delta OD divided by average LED Log 1/T and average IRED Log 1/T, meal data, and occluded measurement data.

30. A non-invasive measurement instrument for measuring a blood analyte concentration, comprising:

a first light source for introducing near-infrared (NIR) energy into blood present in a body part of an individual;

a second light source for introducing red light energy into said blood present in said body part;

a first detector for detecting said NIR energy emerging from said body part, said first detector producing a first electrical signal indicative of said NIR energy emerging from said body part;

a first detector for detecting said NIR energy emerging from said body part, said first detector producing a first electrical signal indicative of said NIR energy emerging from said body part;

a second detector for detecting said red light energy emerging from said body part, said second detector producing a second electrical signal indicative of said red light energy emerging from said body part; and

a processor for calculating a plurality of indicator variables from said first electrical signal and said second electrical signal, determining which indicator variable from said plurality of indicator variables has the highest correlation to blood glucose level, and calculating an estimated value of said blood analyte concentration based on said indicator variable having said highest correlation to blood glucose level,

wherein said blood analyte concentration is calculated using a regression analysis equation.