SYSTEMS AND METHODS FOR IDENTIFYING PATIENT TALKING DURING MEASUREMENT OF A PHYSIOLOGICAL PARAMETER

• US 20140276165A1
• Filed: 03/14/2013
• Published: 09/18/2014
• Est. Priority Date: 03/14/2013
• Status: Abandoned Application

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: Covidien LP (Medtronic Plc)
• Inventors: Addison, Paul S., Watson, James
• Application Number:
  US13/829,012
• Publication Number:
  US 20140276165A1
• Time in Patent Office: Days
• US Class Current: 600/529
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: A61B 7/003 Detecting lung or respiration noise

Abstract

A patient monitoring system may include a microphone that generates a sound signal based on sound emanated from a patient. A patient monitoring unit may process the sound signal to identify respiration information such as respiration rate and to determine whether the patient was talking. If the patient was talking, a confidence value may be calculated, which may be used to generate a respiration information value.

Claims

1. A method for processing a sound signal, the method comprising:

receiving a sound signal from a sensor that senses sound from a patient;

determining, with processing equipment, respiration information based on the sound signal;

identifying, with the processing equipment, a speech portion of the sound signal;

determining, with the processing equipment, a confidence value associated with the respiration information based on the speech portion; and

generating, with the processing equipment, a respiration information value based at least on the confidence value and the respiration information.

2. The method of claim 1, wherein identifying the speech portion of the sound signal comprises:

extracting a respiration signal from the sound signal;

identifying a plurality of breaths from the respiration signal;

determining a distribution of periods associated with the plurality of breaths; and

identifying the speech portion based at least in part on when the distribution exceeds a distribution threshold.

3. The method of claim 1, wherein identifying the speech portion of the sound signal comprises:

extracting a respiration signal from the sound signal;

identifying a plurality of breaths from the respiration signal;

determining an inhalation period for each of the plurality of breaths to produce a plurality of inhalation periods;

determining an exhalation period for each of the plurality of breaths to produce a plurality of exhalation periods;

calculating a ratio of the inhalation period and exhalation period for each of the plurality of breaths to produce a plurality of ratios; and

identifying the speech portion based on the plurality of ratios.

4. The method of claim 1, wherein identifying the speech portion of the sound signal comprises:

determining a classification of the sound signal based on a classifier, wherein the classifier is trained based on signal characteristics that correspond to vocal sounds; and

identifying the speech portion based on the classification.

5. The method of claim 4, wherein the classifier comprises one or more of a neural network, a genetic algorithm, stochastic classifiers, probabilistic classifiers, propositional logics, predicate logics, and nearest neighbor classification methods.

6. The method of claim 1, further comprising:

generating a respiration waveform; and

associating an alarm window with the respiration waveform based on the speech portion of the sound signal.

7. The method of claim 1, further comprising:

updating respiration trend data based on the respiration information; and

updating an alarm window associated with the respiration trend data based on the speech portion of the sound signal.

8. A non-transitory computer-readable storage medium for processing a sound signal, the computer-readable medium having computer program instructions recorded thereon for:

receiving a sound signal from a sensor that senses sound from a patient;

determining respiration information based on the sound signal;

identifying a speech portion of the sound signal;

determining a confidence value associated with the respiration information based on the speech portion; and

generating a respiration information value based at least on the confidence value and the respiration information.

9. The computer-readable medium of claim 8, wherein identifying the speech portion of the sound signal comprises:

extracting a respiration signal from the sound signal;

identifying a plurality of breaths from the respiration signal;

determining a distribution of periods associated with the plurality of breaths; and

identifying the speech portion based at least in part on when the distribution exceeds a distribution threshold.

10. The computer-readable medium of claim 8, wherein identifying the speech portion of the sound signal comprises:

extracting a respiration signal from the sound signal;

identifying a plurality of breaths from the respiration signal;

determining an inhalation period for each of the plurality of breaths to produce a plurality of inhalation periods;

determining an exhalation period for each of the plurality of breaths to produce a plurality of exhalation periods;

calculating a ratio of the inhalation period and exhalation period for each of the plurality of breaths to produce a plurality of ratios; and

identifying the speech portion based on the plurality of ratios.

11. The computer-readable medium of claim 8, wherein identifying the speech portion of the sound signal comprises:

determining a classification of the sound signal based on a classifier, wherein the classifier is trained based on signal characteristics that correspond to vocal sounds; and

identifying the speech portion based on the classification.

12. The computer-readable medium of claim 8, wherein the computer-readable medium has computer program instructions recorded thereon for:

generating a respiration waveform; and

associating an alarm window with the respiration waveform based on the speech portion of the sound signal.

13. The computer-readable medium of claim 8, wherein the computer-readable medium has computer program instructions recorded thereon for:

updating respiration trend data based on the respiration information; and

updating an alarm window associated with the respiration trend data based on the speech portion of the sound signal.

14. A monitoring unit comprises processing equipment configured to:

receive a sound signal from a sensor that senses sound from a patient;

determine respiration information based on the sound signal;

identify a speech portion of the sound signal;

determine a confidence value associated with the respiration information based on the speech portion; and

generate a respiration information value based at least on the confidence value and the respiration information.

15. The monitoring unit of claim 14, wherein the monitoring unit is configured to:

extract a respiration signal from the sound signal;

identify a plurality of breaths from the respiration signal;

determine a distribution of periods associated with the plurality of breaths; and

identify the speech portion based at least in part on when the distribution exceeds a distribution threshold.

16. The monitoring unit of claim 14, wherein the monitoring unit is configured to:

extract a respiration signal from the sound signal;

identify a plurality of breaths from the respiration signal;

determine an inhalation period for each of the plurality of breaths to produce a plurality of inhalation periods;

determine an exhalation period for each of the plurality of breaths to produce a plurality of exhalation periods;

calculate a ratio of the inhalation period and exhalation period for each of the plurality of breaths to produce a plurality of ratios; and

identify the speech portion based on the plurality of ratios.

17. The monitoring unit of claim 14, wherein the monitoring unit is configured to:

determine a classification of the sound signal based on a classifier, wherein the classifier is trained based on signal characteristics that correspond to vocal sounds; and

identify the speech portion based on the classification.

18. The monitoring unit of claim 17, wherein the classifier comprises one or more of a neural network, a genetic algorithm, stochastic classifiers, probabilistic classifiers, propositional logics, predicate logics, and nearest neighbor classification methods.

19. The monitoring unit of claim 14, wherein the monitoring unit is configured to:

generate a respiration waveform; and

associate an alarm window with the respiration waveform based on the speech portion of the sound signal.

20. The monitoring unit of claim 14, wherein the monitoring unit is configured to:

update respiration trend data based on the respiration information; and

update an alarm window associated with the respiration trend data based on the speech portion of the sound signal.