Method of analyzing and processing signals

• US 9,220,459 B2
• Filed: 08/20/2012
• Issued: 12/29/2015
• Est. Priority Date: 02/27/2003
• Status: Active Grant

• Current Assignee: Nellcor Puritan Bennett Ireland
• Original Assignee: Nellcor Puritan Bennett Ireland
• Inventors: Addison, Paul Stanley, Watson, James Nicholas
• Primary Examiner(s): D'ANGELO, MICHAEL J
• Application Number:
  US13/590,100
• Publication Number:
  US 20130046184A1
• Time in Patent Office: 1,226 Days
• Field of Search: 600/323, 600/309, 600/310, 600/324, 600/481, 600/502, 600/529, 600/534
• US Class Current: 1/1
• CPC Class Codes: A61B 2503/06 Children, e.g. for attention deficit diagnosis
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/0082 adapted for particular medical purposes
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• 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 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/6826 Finger
• CPC Class Codes: A61B 5/6829 Foot or ankle
• CPC Class Codes: A61B 5/6838 Clamps or clips
• CPC Class Codes: A61B 5/6896 Toys
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: A61B 5/7214 using signal cancellation, e.g. based on input of two identical physiological sensors spaced apart, or based on two signals derived from the same sensor, for different optical wavelengths
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: G01N 21/3151 using two sources of radiation of different wavelengths G01N21/33 - G01N21/39 take precedence

Abstract

A physiological measurement system is disclosed which can take a pulse oximetry signal such as a photoplethysmogram from a patient and then analyze the signal to measure physiological parameters including respiration, pulse, oxygen saturation and movement. The system comprises a pulse oximeter which includes a light emitting device and a photodetector attachable to a subject to obtain a pulse oximetry signal; analogue to digital converter means arranged to convert said pulse oximetry signal into a digital pulse oximetry signal; signal processing means suitable to receive said digital pulse oximetry signal and arranged to decompose that signal by wavelet transform means; feature extraction means arranged to derive physiological information from the decomposed signal; an analyzer component arranged to collect information from the feature extraction means; and data output means arranged in communication with the analyzer component.

Claims

1. A method for determining physiological information, comprising:

obtaining, using a signal processor, a photoplethysmographic (PPG) biosignal from a subject at least in part using a signal acquisition unit;

decomposing, using the signal processor, the PPG biosignal at least in part using a first wavelet transform analysis to generate first transform data;

decomposing, using the signal processor, the PPG biosignal at least in part using a second wavelet transform analysis to generate second transform data;

analyzing, using the signal processor, the first transform data and the second transform data; and

selecting, using the signal processor, features of at least one of the first transform data and the second transform data based at least in part on the analysis to determine physiological information of the subject wherein the physiological information comprises at least one of heart rate of the subject, breathing rate of the subject, and blood oxygen saturation of the subject.

2. The method of claim 1, further comprising identifying, using the signal processor, a path on a scalogram, wherein decomposing the PPG biosignal at least in part using the second wavelet transform analysis comprises decomposing the path using the second wavelet transform analysis.

3. The method of claim 2, wherein the path comprises a ridge of a band or a path in a vicinity of a ridge of a band.

4. The method of claim 2, wherein the path comprises time-scale points or time-amplitude points.

5. The method of claim 1, wherein:

analyzing, using the signal processor, at least one of the first transform data and the second transform data comprises determining whether an artifact interferes with a band of interest; and

selecting, using the signal processor, features of at least one of the first transform data and the second transform data comprises selecting a band that contains the least interference.

6. The method of claim 1, wherein:

analyzing, using the signal processor, at least one of the first transform data and the second transform data comprises determining a confidence measure associated with the first wavelet transform analysis and the second wavelet transform analysis; and

selecting, using the signal processor, features of at least one of the first transform data and the second transform data comprises selecting the features based at least in part on the confidence measure.

7. The method of claim 6, wherein:

decomposing, using the signal processor, the PPG biosignal at least in part using a first wavelet transform analysis comprises decomposing a first path on a scalogram derived from the biosignal;

decomposing, using the signal processor, the PPG biosignal at least in part using a second wavelet transform analysis comprises decomposing a second path on a scalogram derived from the PPG biosignal; and

determining, using the signal processor, the confidence measure comprises analyzing the first and second paths.

8. The method of claim 7, wherein the confidence measure is determined based at least in part on the entropy of the first and second paths.

9. The method of claim 7, wherein the confidence measure is determined by analyzing a band in the first transform data and a band in the second transform data.

10. The method of claim 1, wherein selecting features of at least one of the first transform data and the second transform data based at least in part on the analysis comprises using a decision tree implementing a weighted branching based on features of the first transform data and the second transform data.

11. The method of claim 1, wherein the signal acquisition unit comprises a photodetector, the method further comprising determining respiration information based at least in part on the selected features.

12. The method of claim 1, further comprising using the selected features within a time window and reassessing the selected features at the end of the time window.

13. A monitoring system for determining physiological information, the system comprising:

a signal acquisition unit attachable to a subject to obtain a photoplethysmoraphic (PPG) biosignal; and

a signal processor configured to;

decompose the PPG biosignal at least in part using a first wavelet transform analysis to generate first transform data;

decompose the PPG biosignal at least in part using second wavelet transform analysis to generate a second transform data;

analyze the first transform data and the second transform data; and

select features of at least one of the first transform data and the second transform data based at least in part on the analysis to determine physiological information of the subject, wherein the physiological information comprises at least one of heart rate of the subject, breathing rate of the subject, and blood oxygen saturation of the subject.

14. The system of claim 13, wherein the signal processor is further configured to identify a path on a scalogram, wherein the signal processor is configured to decompose the PPG biosignal at least in part using the second wavelet transform analysis by decomposing the path using the second wavelet transform analysis.

15. The system of claim 14, wherein the path comprises a ridge of a band or a path in a vicinity of a ridge of a band.

16. The system of claim 14, wherein the path comprises time-scale points or time-amplitude points.

17. The system of claim 13, wherein the signal processor is configured to:

analyze the at least one of the first transform data and the second transform data by determining whether an artifact interferes with a band of interest; and

select the features of at least one of the first transform data and the second transform data by selecting a band that contains the least interference.

18. The system of claim 13, wherein the signal processor is configured to:

analyze the at least one of the first transform data and the second transform data by determining a confidence measure associated with the first wavelet transform analysis and the second wavelet transform analysis; and

select the features of at least one of the first transform data and the second transform data by selecting the features based at least in part on the confidence measure.

19. The system of claim 13, wherein the signal processor is configured to:

decompose the PPG biosignal at least in part using a first wavelet transform analysis by decomposing a first path on a scalogram derived from the PPG biosignal;

decompose the PPG biosignal at least in part using a second wavelet transform analysis by decomposing a second path on a scalogram derived from the PPG biosignal; and

determine the confidence measure by analyzing the first and second paths.

20. The system of claim 19, wherein the confidence measure is determined based at least in part on the entropy of the first and second paths.

21. The system of claim 19, wherein the confidence measure is determined by analyzing a band in the first transform data and a band in the second transform data.

22. The system of claim 13, wherein the signal processor is configured to select features of at least one of the first transform data and the second transform data based at least in part on the analysis by using a decision tree implementing a weighted branching based on features of the first transform data and the second transform data.

23. The system of claim 13, wherein the signal acquisition unit comprises a photodetector and wherein the PPG biosignal is a photoplethysmogram signal, wherein the signal processor is further configured to determine respiration information based at least in part on the selected features.

24. The system of claim 13, wherein the signal processor is further configured to use the selected features within a time window and reassess the selected features at the end of the time window.