Modulation ratio determination with accommodation of uncertainty

• US 20080081325A1
• Filed: 09/29/2006
• Published: 04/03/2008
• Est. Priority Date: 09/29/2006
• Status: Active Grant

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: Nellcor Puritan Bennett Incorporated (Medtronic Plc)
• Inventors: Mannheimer, Paul D., Pav, Steven E.
• Granted Patent: US 7,848,891 B2
• Time in Patent Office: Days
• US Class Current: 435/4
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/6826 Finger
• CPC Class Codes: A61B 5/6838 Clamps or clips

Abstract

Embodiments of the present invention relate to a system and method for detecting a blood characteristic in a patient. Embodiments of the present invention may comprise detecting a first modulating signal at a first wavelength, detecting a second modulating signal at a second wavelength, and determining a relative amplitude of the first and second modulating signals. Further, embodiments of the present invention may comprise regressing the first and second modulating signals relative to one another, wherein a first uncertainty value in the first modulating signal and a second uncertainty value in the second modulating signal are accommodated.

Claims

1. A method of detecting a blood characteristic in a patient, comprising:

detecting a first modulating signal at a first wavelength;

detecting a second modulating signal at a second wavelength; and

determining a relative amplitude of the first and second modulating signals comprising;

regressing the first and second modulating signals relative to one another, wherein a first uncertainty value in the first modulating signal and a second uncertainty value in the second modulating signal are accommodated.

2. The method of claim 1, comprising determining a best-fit relationship based on the regressing of the first and second modulating signals.

3. The method of claim 2, comprising calculating a blood oxygen level, a carboxyhemoglobin level, a methemoglobin level, a total hemoglobin, a bilirubin level, a glucose level, a pH, or CO₂ level based on the best-fit relationship.

4. The method of claim 1, wherein the first and second modulating signals comprise photoplethysmographic signals.

5. The method of claim 1, wherein the first uncertainty value is non-zero and the second uncertainty value is non-zero.

6. The method of claim 1, wherein the first and second uncertainty values are not equal.

7. The method of claim 1, wherein regressing the first and second modulating signals includes performing an orthogonal fit.

8. The method of claim 1, wherein regressing the first and second modulating signals includes performing a Weighted Principal Component regression.

9. The method of claim 1, wherein regressing the first and second modulating signals includes determining mean values of data points from the first and second modulating signals.

10. The method of claim 9, comprising defining a mean data point from the meanvalues of the data points and defining vectors from the mean data point to each of the data points.

11. The method of claim 1, comprising calculating a blood oxygen level based on the relative amplitude.

12. A system for detecting a blood characteristic in a patient, comprising:

a detector configured to detect a first modulating signal at a first wavelength and a second modulating signal at a second wavelength after dispersion of the first modulating signal and the second modulating signal by tissue; and

a monitor configured to regress the first and second modulating signals relative to one another while accommodating a first uncertainty value in the first modulating signal and a second uncertainty value in the second modulating signal to determine a relative amplitude of the first and second modulating signals;

13. The system of claim 12, wherein the monitor is configured to determine a best-fit relationship based on the regressing of the first and second modulating signals.

14. The system of claim 12, wherein the monitor is configured to calculate a blood oxygen level, a carboxyhemoglobin level, a methemoglobin level, a total hemoglobin, a bilirubin level, a glucose level, a pH, or CO₂ level based on the best-fit relationship.

15. The system of claim 12, wherein the first uncertainty value is non-zero and the second uncertainty value is non-zero.

16. The system of claim 12, wherein the first and second uncertainty values are not equal.

17. The system of claim 12, wherein the monitor is configured to regress the first and second modulating signals by performing an orthogonal fit.

18. The system of claim 12, wherein the monitor is configured to regress the first and second modulating signals by performing a Weighted Principal Component regression.

19. The system of claim 12, wherein the monitor is configured to regress the first and second modulating signals by determining mean values of data points from the first and second modulating signals.

20. The system of claim 19, wherein the monitor is configured to define a mean data point from the meanvalues of the data points and define vectors from the mean data point to each of the data points.

21. The system of claim 12, wherein the monitor is configured to calculate a blood oxygen level based on the relative amplitude.

22. The system of claim 12, comprising an emitter configured to emit the first modulating signal at the first wavelength and the second modulating signal at the second wavelength into the tissue.

23. A method of detecting a blood characteristic in a patient, comprising:

emitting a first modulating signal at a first wavelength into tissue;

emitting a second modulating signal at a second wavelength into the tissue;

detecting the first modulating signal after dispersion by the tissue;

detecting the second modulating signal after dispersion by the tissue;

regressing the first and second modulating signals relative to one another, wherein a first uncertainty value in the first modulating signal and a second uncertainty value in the second modulating signal are accommodated; and

determining a relative amplitude of the first and second modulating signals based on the regressing of the first and second modulating signals relative to one another.

24. The method of claim 23, comprising determining a best-fit relationship based on the regressing of the first and second modulating signals.

25. The method of claim 23, wherein the first uncertainty value is non-zero and the second uncertainty value is non-zero.

26. The method of claim 23, wherein the first and second uncertainty values are not equal.

27. The method of claim 23, wherein regressing the first and second modulating signals includes performing an orthogonal fit.

28. The method of claim 23, wherein regressing the first and second modulating signals includes performing a Weighted Principal Component regression.

29. The method of claim 23, wherein regressing the first and second modulating signals includes determining mean values of data points from the first and second modulating signals.