Respiration processor

Patent metadata

Field	Value
Publication number	US-9724016-B1
Application number	US-90538410-A
Country	US
Kind code	B1
Filing date	Oct 15, 2010
Priority date	Oct 16, 2009
Publication date	Aug 8, 2017
Grant date	Aug 8, 2017

Abstract

Respiratory rate can be calculated from an acoustic input signal using time domain and frequency domain techniques. Confidence in the calculated respiratory rate can also be calculated using time domain and frequency domain techniques. Overall respiratory rate and confidence values can be obtained from the time and frequency domain calculations. The overall respiratory rate and confidence values can be output for presentation to a clinician.

First claim

What is claimed is:

1. A method of calculating respiratory rates, the method comprising:
receiving, by a processor, an acoustic signal from an acoustic respiratory sensor coupled with a medical patient;
estimating, by the processor, first respiratory rates from the acoustic signal using a first frequency domain representation of the acoustic signal;
estimating, by the processor, second respiratory rates from the acoustic signal using a second frequency domain representation of the acoustic signal, the second frequency domain representation of the acoustic signal derived from samples of the acoustic signal sensed over a longer period of time than samples of the acoustic signal used to derive the first frequency domain representation of the acoustic signal;
calculating, by the processor, first confidence values associated with the first respiratory rates based at least in part on a comparison between first harmonic energy and first total energy in frequency spectrums of the first frequency domain representation of the acoustic signal, the first harmonic energy comprising energy of one or more harmonics in the frequency spectrums;
calculating, by the processor, second confidence values associated with the second respiratory rates based at least in part on a comparison between second harmonic energy and second total energy in frequency spectrums of the second frequency domain representation of the acoustic signal, the second harmonic energy comprising energy of one or more harmonics in the frequency spectrums;
generating, by the processor, a point cloud including the first respiratory rates and the second respiratory rates;
selecting, by the processor, overall respiratory rates from the first respiratory rates and the second respiratory rates based at least in part on comparisons between the first confidence values and the second confidence values and comparisons between trends in the first respiratory rates in the point cloud and trends in the second respiratory rates in the point cloud; and
outputting, by the processor, the overall respiratory rates to a display for presentation on the display;
wherein at least some of the same set of samples of the acoustic signal are used to estimate the first respiratory rates and the second respiratory rates and to calculate the first confidence values and the second confidence values.

2. The method of claim 1 , wherein estimating at least one of the first respiratory rates comprises identifying a first peak in one of the frequency spectrums, the first peak having one or more harmonics.

3. The method of claim 2 , further comprising assigning a frequency of the first peak as the at least one of the first respiratory rates.

4. The method of claim 2 , wherein said estimating the at least one of the first respiratory rates further comprises identifying a second peak at half a frequency of the first peak in the one of the frequency spectrums, and assigning the frequency of the second peak as the at least one of the first respiratory rates.

5. The method of claim 1 , wherein calculating at least one of the first confidence values comprises calculating a confidence value indicating a greater confidence that at least one of the first respiratory rates reflects an actual respiratory rate of the medical patient when the first harmonic energy in one of the frequency spectrums is relatively greater compared to the total energy in the one of the frequency spectrums than when the first harmonic energy in the one of the frequency spectrums is relatively lesser compared to the total energy in the one of the frequency spectrums.

6. A method of calculating respiratory rates, the method comprising:
estimating, by a processor, first respiratory rates using a frequency domain representation of an acoustic signal from one or more acoustic sensors coupled with a patient, the acoustic signal reflecting physiological sounds generated by the patient;
estimating, by the processor, second respiratory rates from the acoustic signal using a different technique than is used to estimate the first respiratory rate, wherein said estimating the second respiratory rates comprises using a time domain representation of the acoustic signal;
assigning, by the processor, first confidence values associated with the estimated first respiratory rates;
assigning, by the processor, second confidence values associated with the estimated second respiratory rates by at least:
determining magnitudes of local maximums in the time domain representation of the acoustic signal, and
assigning the second confidence values based at least in part on a comparison between the magnitudes of the local maximums and one or more magnitude thresholds;

selecting, by the processor, overall respiratory rates based at least in part on the estimated first respiratory rates, the first confidence values, the estimated second respiratory rates, and the second confidence values by at least:
fitting a first curve to the estimated first respiratory rates using the first confidence values to weight fits of the estimated first respiratory rates to the first curve,
fitting a second curve to the estimated second respiratory rates using the second confidence values to weight fits of the estimated second respiratory rates to the second curve, and
selecting the overall respiratory rates from the estimated first respiratory rates and the estimated second respiratory rates according at least to characteristics of the first curve and the second curve; and

outputting, by the processor, the overall respiratory rates to a display for presentation on the display.

7. The method of claim 6 , wherein estimating at least one of the second respiratory rates comprises identifying time differences between local maximums in the time domain representation of the acoustic signal.

8. The method of claim 7 , wherein said identifying the time differences comprises performing a weighted average of the time differences between the local maximums occurring within a time window.

9. The method of claim 7 , further comprising identifying at least some of the local maximums as glitches and filtering the glitches to reduce their impact on said estimating the at least one of the second respiratory rates.

10. The method of claim 6 , wherein assigning at least one of the second confidence values further comprises:
in response to determining that a magnitude of one of the local maximums exceeds a first magnitude threshold and does not exceed a second magnitude threshold, assigning a confidence value indicating a relatively greater confidence that at least one of the estimated second respiratory rates reflects an actual respiratory rate of the patient; and
in response to determining that the magnitude of the one of the local maximums does not exceed the first magnitude threshold or exceeds the second magnitude threshold, assigning a confidence value indicating a relatively lower confidence that the at least one of the second respiratory rates reflects the actual respiratory rate of the patient.

11. The method of claim 10 , further comprising varying the first and second magnitude thresholds based at least in part on a noise floor, and wherein said assigning the at least one of the second confidence values comprises assigning a confidence value indicating no confidence that the at least one of the second respiratory rates reflects the actual respiratory rate of the patient in response to determining that the magnitude of the one of the local maximums does not exceed the noise floor.

12. The method of claim 10 , wherein said assigning the at least one of the second confidence values comprises assigning the confidence value so that a value ass

Assignees

• Al-Ali Ammar
• Weber Walter M
• Majmudar Anmol B
• Sierra Gilberto
• Lee Sung Uk
• Diab Mohamed
• Telfort Valery G
• Pelletier Marc
• Popov Boris
• Masimo Corp

Inventors

• Al-Ali Ammar
• Weber Walter M
• Majmudar Anmol B
• Sierra Gilberto
• Lee Sung Uk
• Diab Mohamed
• Telfort Valery G
• Pelletier Marc
• Popov Boris

Classifications

• A61B7/003

  Detecting lung or respiration noise · CPC title

• A61B5/7257

  using Fourier transforms · CPC title

• A61B5/7221

  Determining signal validity, reliability or quality (preventing, reducing or removing noise induced by motion artefacts A61B5/7207; noise originating from a therapeutic or surgical apparatus A61B5/7217) · CPC title

• A61B5/0816 Primary

  Measuring devices for examining respiratory frequency (measuring frequency of electric signals G01R23/00) · CPC title

• A61B5/08

  Measuring devices for evaluating the respiratory organs · CPC title