Method and apparatus for estimating physiological parameters using model-based adaptive filtering

• US 6,836,679 B2
• Filed: 02/05/2002
• Issued: 12/28/2004
• Est. Priority Date: 08/07/1995
• Status: Expired due to Term

• Current Assignee: Nellcor Puritan Bennett Incorporated (Medtronic Plc)
• Original Assignee: Nellcor Puritan Bennett Incorporated (Medtronic Plc)
• Inventors: Yorkey, Thomas J., Baker, Clark R. Jr.
• Primary Examiner(s): Hindenburg, Max F.
• Assistant Examiner(s): KREMER, MATTHEW J
• Application Number:
  US10/072,589
• Publication Number:
  US 20020137994A1
• Time in Patent Office: 1,057 Days
• Field of Search: 600/309-310, 600/322-324, 600/330, 600/336, 600/504, 600/507, 600/500
• US Class Current: 600/323
• CPC Class Codes: A61B 5/0075 by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy A61B5/0071 takes precedence
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/14552 Details of sensors specially adapted therefor
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: A61B 5/7239 using differentiation including higher order derivatives
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: H03H 21/003 KALMAN filters

Abstract

A method and apparatus for reducing the effects of noise on a system for measuring physiological parameters, such as, for example, a pulse oximeter. The method and apparatus of the invention take into account the physical limitations on various physiological parameters being monitored when weighting and averaging a series of measurements. Varying weights are assigned different measurements, measurements are rejected, and the averaging period is adjusted according to the reliability of the measurements. Similarly, calculated values derived from analyzing the measurements are also assigned varying weights and averaged over adjustable periods. More specifically, a general class of filters such as, for example, Kalman filters, is employed in processing the measurements and calculated values. The filters use mathematical models which describe how the physiological parameters change in time, and how these parameters relate to measurement in a noisy environment. The filters adaptively modify a set of averaging weights to optimally estimate the physiological parameters.

Claims

1. A method for determining oxygen saturation comprising:

detecting first and second electromagnetic radiation signals from a patient corresponding to infrared and red wavelengths of light;

converting said first and second electromagnetic radiation signals into first and second digital signals;

filtering said first and second digital signals;

normalizing said first and second digital signals;

determining a first oxygen saturation value using a first saturation calculation algorithm applied to said first and second digital signals;

determining a second oxygen saturation value using a second saturation calculation algorithm applied to said first and second digital signals;

arbitrating between said first and second oxygen saturation values based on a saturation confidence associated with said first and second oxygen saturation values to select a best oxygen saturation value;

determining a first pulse rate from said first and second digital signals using a first pulse rate algorithm;

determining a second pulse rate from said first and second digital signals using a second pulse rate algorithm; and

arbitrating between said first and second pulse rates based on a pulse rate confidence associated with said first and second pulse rate signals to select a best pulse rate.

2. The method of claim 1 wherein said first saturation calculation algorithm includes performing adaptive filtering.

3. The method of claim 1 wherein said second saturation calculation algorithm utilizes the ratio of ratios.

4. The method of claim 1 wherein said first pulse rate algorithm analyzes a waveform of said first and second digital signals.

5. The method of claim 1 wherein said second pulse rate algorthm analyzes a frequency of said first and second digital signals.

6. The method of claim 5 wherein said second pulse rate algorithm utilizes a comb filter.

7. The method of claim 1 wherein said saturation confidence and said pulse rate confidence are based on noise characteristics of said first and second digital signals.

8. The method of claim 1 further comprising:

providing a first confidence level associated with said first oxygen saturation value; and

providing a second confidence level associated with said second oxygen saturation value;

wherein the arbitrating comprises;

comparing the first and second confidence levels; and

selecting as the best oxygen saturation value one associated with one of the first and second confidence levels which is greater than the other of the first and second confidence levels by at least a first amount.

9. The method of claim 1 further comprising:

cancelling out a noise signal from at least one of said first and second digital signals.

10. A method for determining oxygen saturation comprising:

detecting first and second electromagnetic radiation signals from a patient corresponding to infrared and red wavelengths of light;

converting said first and second electromagnetic radiation signals into first and second digital signals;

filtering said first and second digital signals;

normalizing said first and second digital signals;

cancelling out a noise signal from at least one of said first and second digital signals;

determining a first oxygen saturation value using a first saturation calculation algorithm using adaptive filtering applied to said first and second digital signals;

determining a second oxygen saturation value using a second saturation calculation algorithm using the ratio of ratios applied to said first and second digital signals;

providing a first confidence level associated with said first oxygen saturation value;

providing a second confidence level associated with said second oxygen saturation value;

comparing the first and second confidence levels;

arbitrating between said first and second oxygen saturation values, based on which of said first and second confidence levels is greater than the other of the first and second confidence levels by at least a first amount, to select a best oxygen saturation value;

determining a first pulse rate from said first and second digital signals using a first pulse rate algorithm;

determining a second pulse rate from said first and second digital signals using a second pulse rate algorithm;

arbitrating between said first and second pulse rates based on a pulse rate confidence associated with said first and second pulse rate signals to select a best pulse rate;

performing post processing on said best oxygen saturation value;

providing said best oxygen saturation value to a display; and

providing said best pulse rate value to said display.

11. The method of claim 10 wherein:

said first pulse rate algorithm analyzes a waveform of said fir an second digital signals;

said second pulse rate algorithm analyzes a frequency of said first and second digital signals utilizing a comb filter.

12. A method for measuring a blood constituent, the method comprising:

determining a plurality of possible blood constituent values using a plurality of blood constituent value calculators, each of the possible blood constituent values having a confidence level associated therewith based on at least one quality metric; and

arbitrating between the plurality of possible blood constituent values with regard to the confidence levels to determine a measure of the blood constituent, wherein the arbitrating comprises linearly interpolating between the plurality of possible blood constituent values to generate the measure of the blood constituent where none of the confidence levels is greater than all other confidence levels by more than a first amount.

13. An apparatus for measuring a blood constituent using a single data set, comprising:

means for determining a plurality of possible blood constituent values using a plurality of blood constituent value calculators, each of the blood constituent value calculators using the single data set, each of the possible blood constituent values having a confidence level associated therewith based on at least one quality metric; and

means for arbitrating between the plurality of possible blood constituent values with regard to the confidence levels to determine a measure of the blood constituent.

14. A method for determining a patient setrate using signals corresponding to energy transmitted through the tissue of a patient the method comprising:

determining a plurality of possible pulse rates using a plurality of pulse rate finders, each of the possible pulse rates having a confidence level associated therewith based on at least one quality metric; and

arbitrating between the plurality of possible pulse rates with regard to the confidence levels to determine the patient'"'"'s pulse rate, wherein the arbitrating comprises linearly interpolating between the plurality of possible pulse rates to generate the patient'"'"'s pulse rate where none of the confidence levels is greater than all other confidence levels by more than a first amount.

15. A method for determining a patient'"'"'s pulse rate using data corresponding to energy transmitted through the tissue of a patient, the method comprising:

determining a plurality of possible pulse rates using a plurality of pulse rate finders, each of the possible pulse rates having a confidence level associated therewith based on at least one quality metric; and

arbitrating between the plurality of possible pulse rates with regard to the confidence levels to determine the patient'"'"'s pulse rate, wherein one pulse rate finder determines its corresponding possible pulse rate by;

defining a comb filter to remove signal energy from the data corresponding to a fundamental frequency and harmonics thereof;

determining a particular harmonic frequency which minimizes noise energy at an output of the comb filter, the particular harmonic frequency corresponding to the fundamental frequency; and

generating the possible pulse rate corresponding to the particular harmonic frequency.

16. The method of claim 15 wherein the determining a particular harmonic frequency comprises:

calculating squared noise for the data;

calculating a second derivative of the squared noise with respect to the fundamental frequency; and

performing a Newton-Raphson search to determine the particular harmonic frequency.

17. The method of claim 15 further comprising:

evaluating a power spectrum corresponding to the data to determine which of a plurality of peaks in the power spectrum corresponds to the fundamental frequency; and

verifying that the particular harmonic frequency corresponds to the fundamental frequency based on said evaluating.

18. The method of claim 15 wherein the at least one quality metric is selected from the group consisting of pulse signI shape, signal-to-noise ratio, correlation of at least one wavelength of electromagnetic energy, and arrhythmia probability.

19. The method of claim 15 wherein there are two wavelengths of electromagnetic energy, and the at least one quality metric comprises a correlation between the data corresponding to the two wavelengths.

20. A method for determining a patient'"'"'s pulselrate using data corresponding to energy transmitted through the tissue of a patient, the method comprising:

determining a plurality of possible pulse rates using a plurality of pulse rate finders, each of the possible pulse rates having a confidence level associated therewith based on at least one quality metric; and

arbitrating between the plurality of possible pulse rates with regard to the confidence levels to determine the patient'"'"'s pulse rate, wherein one pulse rate finder determines its corresponding possible pulse rate by;

comparing the data to a predetermined waveform template;

identifying a sequence of waveform characteristics indicative of a waveform period;

averaging a number of successive waveform periods to determine an average waveform period; and

determining the corresponding possible pulse rate from the average waveform period.

21. The method of claim 20 wherein the at least one quality metric is selected from the group consisting of a motion indication, and a proportion of motion corrupted pulse periods detected over a time interval.

22. A method for determining a pulse rate of a patient using data corresonding to at least one wavelength of electromagnetic energy transmitted through tissue of the patient, the method comprising:

tracking a fundamental frequency using an adaptive comb filter to filter the data and to thereby generate a first pulse rate, the first pulse rate having a first confidence level associated therewith based on at least one quality metric;

comparing the data to a predetermined waveform template to generate a second pulse rate, the second pulse rate having a second confidence level associated therewith based on the at least one quality metric; and

arbitrating between the first and second pulse rates with regard to the first and second confidence levels to determine the patient'"'"'s pulse rate.

23. The method of claim 22 wherein the tracking comprises:

defining a comb filter to remove signal energy from the data corresponding to the fundamental frequency and harmonics thereof; and

determining a particular harmonic frequency which minimizes noise energy at an output of the comb filter, the particular harmonic frequency corresponding to the fundamental frequency.

24. The method of claim 23 wherein the determining comprise:

calculating squared noise for the data;

calculating a second derivative of the squared noise with respect to the fundamental frequency; and

performing a Newton-Raphson search to determine the fundamental frequency.

25. The method of claim 23 wherein the tracking comprises:

evaluating a power spectrum corresponding to the data to determine which of a plurality of peaks in the power spectrum corresponds to the fundamental frequency; and

verifying that the particular harmonic frequency corresponds to the fundamental frequency based on said evaluating.

26. The method of claim 22 wherein the tracking comprises Kafman filtering the first pulse rate to determine a filtered first pulse rate.

27. The method of claim 22 wherein the comparing comprises:

identifying a sequence of waveform characteristics indicative of a waveform period;

averaging a number of successive waveform periods to determine an average waveform period; and

determining the second pulse rate from the average waveform period.

28. The method of claim 22 wherein the arbitrating comprise:

comparing the first and second confidence levels; and

selecting as the patient'"'"'s pulse rate one of the first and second confidence levels which is greater than the other of the first and second confidence levels by at least a first amount.

30. The method of claim 22 wherein the at least one quality meric corresponding to the first confidence level is seleced from the group consisting of pulse signal shape, signal-to-noise ratio, correlation of the at least one wavelength of electromagnetic energy, and arrhythmia probability.

31. The method of claim 22 wherein there are two wavelenths of electromagnetic energy, and the at least one quality metric corresponding to the first confidence level comprises a correlation between the data corresponding to the two wavelengths.

32. The method of claim 22 wherein the at least one quality metric corresponding to the second confidence level is selected from the group consisting of a motion indication and a proportion of motion corrupted pulse periods detected over a time interval.

33. The method of claim 22 further comprising a preprocessing prior to said tracking, wherein said preprocessing comprises:

taking the logarithm of a signal representative of the at least one wavelength of electromagnetic energy, thereby generating a first signal;

band pass filtering the first signal, therebygenerating a second signal; and

normalizing the second signal, thereby generating the data;

and wherein the tracking comprises taking the derivative of the data.

29. The method of 22 wherein the arbitrating comprises linearly interpolating between the first and second plse rates to generate the patient'"'"'s pulse rate where neither of the first and second confidence levels is greater than the other of the first and second confidence levels by more than a first amount.

34. A method for determining oxygen saturation in a pulse oximeter comprising:

detecting first and second electromagnetic radiation signals from a patient corresponding to first and second wavelengths of light;

converting said first and second electromagnetic radiation signals into first and second digital signals;

filtering said first and second digital signals;

determining a first oxygen saturation value using a first saturation calculation algorithm applied to said first and second digital signals;

determining a second oxygen saturation value using a second saturation calculation algorithm applied to said first and second digital signals; and

arbitrating by said oximeter between said first and second oxygen saturation values based on a saturation confidence associated with said first and second oxygen saturation values to select a best oxygen saturation value.

35. The method of claim 34 wherein said second saturation calculation algorithm utilizes the ratio of ratios.

36. The method of claim 34 wherein said saturation confidence is based on noise characteristics of said first and second digital signals.

37. The method of claim 34 wherein said wavelengths are red and infrared.