Method and apparatus for estimating a physiological parameter

• US 20050143634A1
• Filed: 03/01/2005
• Published: 06/30/2005
• Est. Priority Date: 08/07/1995
• Status: Active Grant

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: Nellcor Incorporated (Medtronic Plc)
• Inventors: Yorkey, Thomas J., Baker, Clark R. Jr.
• Granted Patent: US 7,931,599 B2
• Time in Patent Office: Days
• US Class Current: 600/310
• 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

1-17. -17. (canceled)

18. A physiological monitor for monitoring a pulserate of a living being, said monitor comprising a signal processor configured to:

transform a time-domain plethysmograph dataset into a spectral-domain dataset;

identify three or more spectral peaks at non-zero frequencies in said spectral domain dataset; and

sort said three or more spectral peaks according to one or more rules into one or more spectral peaks corresponding to a fundamental frequency and one or more harmonics of said fundamental frequency, and estimate a pulserate from said fundamental frequency and said one or more harmonics.

19. The physiological monitor of claim 18, wherein said one or more rules comprise comparisons of relative magnitudes of one or more of said spectral peaks.

20. In a physiological monitor for measuring a pulserate of a living being, said monitor having a detector producing a detector output waveform corresponding to a time-domain plethysmograph waveform, a method comprising:

transforming a time-domain plethysmograph waveform into a spectral domain waveform;

identifying three or more spectral peaks at non-zero frequencies in said spectral domain waveform;

classifying said three or more spectral peaks into a first group comprising one or more spectral peaks corresponding to a fundamental frequency and a second group comprising one or more harmonics of said fundamental frequency; and

estimating a pulserate from at least said first group.

21. In a physiological monitor for measuring a pulserate of a living being, said monitor having a detector producing a detector output waveform corresponding to a time-domain plethysmograph waveform, a method comprising:

transforming a time-domain plethysmograph waveform into a spectral domain waveform;

identifying a plurality of spectral peaks in said spectral domain waveform;

classifying said plurality of spectral peaks into a first group comprising one or more spectral peaks corresponding to a fundamental frequency and a second group comprising one or more harmonics of said fundamental frequency; and

estimating a pulserate from at least said first group, wherein said plurality of spectral peaks are classified according to ratios.

22. In a physiological monitor for measuring a pulserate of a living being, said monitor having a detector producing a detector output waveform corresponding to a time-domain plethysmograph waveform, a method comprising:

transforming a time-domain plethysmograph waveform into a spectral domain waveform;

identifying a plurality of spectral peaks in said spectral domain waveform;

classifying said plurality of spectral peaks into a first group comprising one or more spectral peaks corresponding to a fundamental frequency and a second group comprising one or more harmonics of said fundamental frequency, and

estimating a pulserate from at least said first group, wherein said spectral domain waveform comprises a first component corresponding to a first frequency of light passed through a portion of said living being, and a second component corresponding to a second frequency of light passed through a portion of said living being, and wherein said plurality of spectral peaks are classified at least in part according to one or more ratios, said one or more ratios corresponding to ratios of at least one or more portions of said first component with at least one or more portions of said second component

23. The method of claim 22, wherein said ratios are classified according to one or more rules.

24. An apparatus for monitoring physiological parameters of a living organism having a pulserate, said apparatus comprising:

means for producing a time-domain plethysmograph waveform;

means for transforming said time-domain plethysmograph waveform into a spectral domain waveform having a fundamental spectral peak corresponding to said pulserate and two or more ancillary spectral peaks, and classifying said fundamental spectral peak and said ancillary spectral peaks to estimate said pulserate.

25. A physiological monitor for monitoring a living being having a pulserate, said monitor comprising a signal processor configured to:

transform a time-domain plethysmograph dataset into a spectral-domain dataset;

classify spectral lines in said spectral-domain dataset into a group of spectral values corresponding to a fundamental and oft two or more harmonics of said fundamental; and

estimate a pulserate from said group of spectral values according to one or more rules.

26. A physiological monitor comprising a signal processor configured to:

transform a time-domain plethysmograph dataset into a spectral-domain dataset;

classify at least three spectral lines in said spectral-domain dataset into a group of spectral values corresponding to a first group of one or more spectral lines and at least one second group of spectral lines, said second group of spectral lines comprising at least one harmonic of said first group; and

estimate said pulserate from said first group and at least one of said second group.

27. In a physiological monitor to monitor pulserate, said monitor having a detector responsive to physiological properties related to light passed through a living being, a method comprising:

transforming a first time-domain plethysmograph waveform into a first spectral domain waveform, said first time-domain plethysmograph waveform corresponding to a first frequency of light passed through a living being;

transforming a second time-domain plethysmograph waveform into a second spectral domain waveform, said second time-domain plethysmograph waveform corresponding to a second frequency of light passed through said living being;

classify one or more spectral values obtained from a ratio of said first spectral domain waveform and said second spectral domain waveform into a series of spectral peaks comprising a fundamental peak and at least one harmonics of said fundamental peak; and

estimating said pulserate from said series of spectral peaks.

28. The method of claim 27, wherein said pulserate is estimated according to a center of mass of at least a portion of said series of spectral peaks.

29. The method of claim 27, wherein an estimate of said pulserate is associated with a confidence factor.

30. The method of claim 27, further comprising computing a confidence factor indicating a likelihood that an estimate for the pulserate represents the actual pulserate of the living being.

31. In a physiological monitor attached to a living organism having a pulserate, said monitor having a detector responsive to physiological properties related to pulserate, a method comprising the steps of:

transforming a time-domain plethysmograph waveform into a spectral domain waveform;

classifying one or more spectral values obtained from said spectral domain waveform; and

using results from a center of mass calculation of at least a portion of said spectral values to estimate said pulserate.

32. A physiological monitor for monitoring comprising a signal processor configured to:

transform a time-domain representation of a plethysmograph waveform into a spectral-domain representation of said plethysmograph waveform, said spectral-domain representation having at least three spectral peaks at non-zero frequencies;

select a selected portion of said spectral-domain representation based on one or more rules relating to characteristics of spectral lines in said selected portion and one or more harmonics of spectral lines in said selected portion; and

estimate said pulserate from said selected portion of said spectral-domain representation.

33. A physiological monitor comprising a signal processor configured to:

transform a first time-domain representation of a first plethysmograph waveform corresponding to a first optical measurement wavelength into a spectral domain to produce a first spectral-domain representation representing said first plethysmograph waveform and transform a second time-domain representation of a second plethysmograph waveform corresponding to a second optical measurement wavelength into said spectral domain to produce a second spectral-domain representation representing said second plethysmograph waveform;

classify spectral data from said first spectral-domain representation and said second spectral-domain representation at least in part according to a ratio of at least a portion of said first spectral-domain representation and at least a portion of said second spectral-domain representation to identify a series of spectral peaks corresponding to a fundamental and at least one or more harmonics of said fundamental; and

estimate said pulserate from said series of spectral peaks as a function of a center of mass type of calculation of at least a portion of said series of spectral peaks.

34. A physiological monitor comprising a signal processor configured to:

transform a first time-domain representation of a first plethysmograph waveform corresponding to a first optical measurement wavelength into a spectral domain to produce a first spectral-domain representation representing said first plethysmograph waveform and a second time-domain representation of a second plethysmograph waveform corresponding to a second optical measurement wavelength into said spectral domain to produce a second spectral-domain representation representing said second plethysmograph waveform;

classify spectral data from said first spectral-domain representation and said second spectral-domain representation at least in part according to a ratio of at least a portion of said first spectral-domain representation and at least a portion of said second spectral-domain representation to identify a series of spectral peaks corresponding to a fundamental and at least one or more additional spectral peaks at frequencies higher than said fundamental; and

compute an estimate of said pulserate from said series of spectral peaks according to said fundamental and at least one of said one or more additional spectral peaks.

35. The physiological monitor of claim 34, said signal processor further configured to calculate a confidence factor related to said estimate of said pulserate.

36. The physiological monitor of claim 34, wherein said series of spectral peaks are classified using one or more rules.

37. The physiological monitor of claim 34, wherein said series of spectral peaks are classified using one or more rules, said one or more rules comprising comparisons of relative magnitudes of one or more of said spectral peaks.

38. The physiological monitor of claim 34, wherein said series of spectral peaks are classified using one or more rules related to said ratio.

39. The physiological monitor of claim 34, wherein said series of spectral peaks are classified using one or more rules related to said ratio and frequencies of said spectral peaks.

40. A physiological monitor for monitoring a pulse rate of a living being, said monitor comprising a signal processor configured to:

perform a Fast Fourier Transform on a time-domain plethysmograph waveform, to obtain a power spectrum having multiple peaks corresponding to a fundamental frequency and one or more harmonics of said fundamental frequency;

apply one or more rules to said multiple peaks to identify a fundamental frequency and the one or more harmonics of said fundamental frequency; and

estimate a pulse rate from said fundamental frequency and said one or more harmonics.

41. The physiological monitor of claim 40, wherein said one or more rules comprise a validity metric, wherein said validity metric is based in part on the strength of said fundamental frequency and said one or more harmonics.

42. A physiological monitor comprising a signal processor configured to:

perform a transformation on a time-domain plethysmograph waveform, to obtain a power spectrum having multiple peaks corresponding to at least three harmonics of a pulse rate of a living being, said multiple peaks corresponding to a fundamental frequency and one or more harmonics of said fundamental frequency;

classify said fundamental frequency and said one or more harmonics of said fundamental frequency by applying one or more rules to said multiple peaks; and

estimate a pulse rate from said fundamental frequency and said one or more harmonics.

43. The physiological monitor of claim 42, wherein said one or more rules comprise a confidence metric, wherein said confidence metric is a function of a validity metric, and wherein said validity metric is based in part on the strength of said fundamental frequency and said one or more harmonics.

44. A physiological monitor for monitoring a pulse rate of a living being, said monitor comprising a signal processor configured to:

perform a transformation on a time-domain plethysmograph waveform, to obtain a power spectrum having multiple peaks corresponding to a fundamental frequency and one or more harmonics of said fundamental frequency;

perform a calculation of a validity metric for said multiple peaks, wherein said validity metric is based in part on the strength of said fundamental frequency and said one or more harmonics; and

estimate a pulse rate using said calculation of said validity metric.

45. A physiological monitor for monitoring a patient'"'"'s pulse rate using time-domain data corresponding to two wavelengths of electromagnetic energy transmitted through the tissue of the patient, said monitor comprising a signal processor configured to:

track the pulse rate in the data using an adaptive comb filter;

periodically calculate a frequency power spectrum of one of said wavelengths;

calculate an autocorrelation function of said wavelengths;

identify peaks in said frequency power spectrum and peaks in said autocorrelation function; and

estimate the pulse rate from said peaks in said frequency power spectrum and said peaks in said autocorrelation function using one or more rules.

46. The physiological monitor of claim 45, wherein said one or more rules are configured for determining said pulse rate as corresponding to the frequency corresponding with a peak present in both said frequency power spectrum and said autocorrelation function.

47. The physiological monitor of claim 45, wherein said processor is configured to calculate a frequency power spectrum using a Fourier transform.

48. The physiological monitor of claim 45, wherein said processor is configured to use the frequency power spectrum to determine which of a plurality of peaks in the frequency power spectrum corresponds to the fundamental frequency.