Systems and methods for determining signal quality of a physiological signal using a wavelet transform and an identified noise floor

• US 8,786,444 B2
• Filed: 01/21/2013
• Issued: 07/22/2014
• Est. Priority Date: 07/15/2008
• Status: Active Grant

• Current Assignee: Nellcor Puritan Bennett Ireland
• Original Assignee: Nellcor Puritan Bennett Ireland
• Inventors: Watson, James Nicholas, Addison, Paul Stanley, McKenna, Edward M., Ochs, James P.
• Primary Examiner(s): HOFSASS, JEFFERY A
• Application Number:
  US13/746,291
• Publication Number:
  US 20130138357A1
• Time in Patent Office: 547 Days
• Field of Search: 340/539.12, 340/573.1, 702/1, 702/19, 600/500
• US Class Current: 340/573.1
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: G06F 2218/06 by applying a scale-space analysis, e.g. using wavelet analysis
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A method and system are provided for evaluating in patient monitoring whether a signal is sensed optimally by receiving a signal, transforming the signal using a wavelet transform, generating a scalogram based at least in part on the transformed signal, identifying a pulse band in the scalogram, identifying a characteristic of the pulse band, determining, based on the characteristic of the pulse band, whether the signal is sensed optimally; and triggering an event. The characteristics of the pulse band and scalogram may be used to provide an indication of monitoring conditions.

Claims

1. A method comprising:

using a processor for;

receiving a physiological signal;

transforming the physiological signal based at least in part on a wavelet transform;

generating scalogram data based at least in part on the transformed signal;

identifying a band in the scalogram data;

identifying a characteristic of the band;

identifying a noise floor of the scalogram data; and

determining signal quality of the physiological signal based at least in part on the characteristic of the band and the noise floor.

2. The method of claim 1 wherein the characteristic of the band comprises one or more of a height of the band, a width of the band, an amplitude of the band, a strength of the band, and a shape of the band.

3. The method of claim 1 wherein the characteristic of the band comprises a width of the band and wherein the signal quality of the physiological signal is inversely related to the width of the band.

4. The method of claim 1 wherein the characteristic of the band is identified by comparing a shape of the band with one or more shape types.

5. The method of claim 1 further comprising:

generating a template of a noiseless slice of the scalogram data based on the physiological signal during one or more periods when noise is not present; and

comparing current scalogram data with the template, wherein determining signal quality is further based at least in part on the comparison.

6. The method of claim 1 further comprising identifying a marker region corresponding to a high amplitude region adjacent to the band, wherein determining signal quality is further based at least in part on the marker region.

7. The method of claim 1 wherein the noise floor is identified outside of the band.

8. The method of claim 1 wherein identifying the noise floor comprises determining a minimum value between two bands in the scalogram data.

9. The method of claim 1 wherein the physiological signal comprises a photoplethysmograph signal.

10. The method of claim 9 wherein the band comprises a pulse band.

11. A system comprising:

a processor capable of;

receiving a physiological signal;

transforming the physiological signal based at least in part on a wavelet transform;

generating scalogram data based at least in part on the transformed signal;

identifying a band in the scalogram data;

identifying a characteristic of the band;

identifying a noise floor of the scalogram data; and

determining signal quality of the physiological signal based at least in part on the characteristic of the band and the noise floor; and

a display for displaying information based at least in part on the physiological signal.

12. The system of claim 11 wherein the characteristic of the band comprises one or more of a height of the band, a width of the band, an amplitude of the band, a strength of the band, and a shape of the band.

13. The system of claim 11 wherein the characteristic of the band comprises a width of the band and wherein the signal quality of the physiological signal is inversely related to the width of the band.

14. The system of claim 11 wherein the characteristic of the band is identified by comparing a shape of the band with one or more shape types.

15. The system of claim 11 wherein the processor is further capable of:

generating a template of a noiseless slice of the scalogram data based on the physiological signal during one or more periods when noise is not present; and

comparing current scalogram data with the template, wherein determining signal quality is further based at least in part on the comparison.

16. The system of claim 11 wherein the processor is further capable of identifying a marker region corresponding to a high amplitude region adjacent to the band, wherein determining signal quality is further based at least in part on the marker region.

17. The system of claim 11 wherein the noise floor is identified outside of the band.

18. The system of claim 11 wherein identifying the noise floor comprises determining a minimum value between two bands in the scalogram data.

19. The system of claim 11 wherein the physiological signal comprises a photoplethysmograph signal detected by a sensor.

20. The system of claim 19 wherein the band comprises a pulse band.