SYSTEMS AND METHODS FOR ARTIFACT DETECTION IN SIGNALS

• US 20090326871A1
• Filed: 10/03/2008
• Published: 12/31/2009
• Est. Priority Date: 06/30/2008
• Status: Active Grant

• Current Assignee: Nellcor Puritan Bennett Ireland
• Original Assignee: Nellcor Puritan Bennett Ireland
• Inventors: Addison, Paul Stanley, Watson, James
• Granted Patent: US 8,827,917 B2
• Time in Patent Office: Days
• US Class Current: 702/191
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• 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

Abstract

According to embodiments, a method and system for artifact detection in signals is disclosed. The artifacts may take the form of movement artifacts in physiological (e.g., pulse oximetry) signals. Artifacts in the wavelet space of the physiological signal may be removed, replaced, ignored, filtered, or otherwise modified by determining the energy within a predefined moving area of the wavelet scalogram, comparing the determined energy within the predefined moving area of the wavelet scalogram to a threshold value, and masking at least one area of artifact in the wavelet scalogram based, at least in part, on the comparison. From the enhanced signal, physiological parameters, for example, respiration, respiratory effort, pulse, and oxygen saturation, may be more reliably and accurately derived or computed.

Claims

1. A method for detecting an artifact in a signal, the method comprising:

transforming the signal using a continuous wavelet transform to generate a transformed signal;

generating a wavelet scalogram based, at least in part, on the transformed signal;

determining energy within a predefined moving area of the wavelet scalogram;

comparing the determined energy within the predefined moving area of the wavelet scalogram to a threshold value; and

masking at least one area of artifact in the wavelet scalogram based, at least in part, on the comparison.

2. The method of claim 1 wherein masking at least one area of artifact in the wavelet scalogram comprises filtering, ignoring, replacing, removing, zeroing out, and/or modifying a portion of the wavelet scalogram.

3. The method of claim 1 further comprising generating an enhanced wavelet scalogram based, at least in part, on the masking.

4. The method of claim 3 further comprising analyzing the enhanced wavelet scalogram to determine at least one physiological parameter.

5. The method of claim 4 wherein the physiological parameter comprises pulse rate, respiration rate, respiratory effort, and/or oxygen saturation.

6. The method of claim 1 wherein determining the energy within a predefined moving area of the wavelet scalogram comprises determining the energy within a moving wedge shaped area of the wavelet scalogram.

7. The method of claim 1 further comprising determining a pulse ridge energy of the wavelet scalogram, wherein the threshold value is based, at least in part, on the determined pulse ridge energy.

8. The method of claim 1 wherein the threshold value is based on at least a local wavelet component and a global wavelet component.

9. The method of claim 8 wherein the local wavelet component is derived from the energy within the predefined moving area of the wavelet scalogram over a first time window, and the global wavelet component is derived from a pulse ridge energy over a second time window, wherein the second time window is longer than the first time window.

10. The method of claim 1 wherein the threshold value is based, at least in part, on a running or moving average of the determined energy within the predefined moving area of the wavelet scalogram.

11. A system for detecting an artifact in a signal, the system comprising:

a sensor capable of generating a signal; and

a processor capable of;

transforming the signal using a continuous wavelet transform to generate a transformed signal;

generating a wavelet scalogram based, at least in part, on the transformed signal;

determining energy within a predefined moving area of the wavelet scalogram;

comparing the determined energy within the predefined moving area of the wavelet scalogram to a threshold value; and

masking at least one area of artifact in the wavelet scalogram based, at least in part, on the comparison.

12. The system of claim 11 wherein the processor is capable of masking at least one area of artifact in the wavelet scalogram by filtering, ignoring, replacing, zeroing out, and/or modifying a portion of the wavelet scalogram.

13. The system of claim 11 wherein the processor is capable of generating an enhanced wavelet scalogram based, at least in part, on the masking.

14. The system of claim 13 wherein the processor is capable of analyzing the enhanced wavelet scalogram to determine at least one physiological parameter.

15. The system of claim 14 wherein the physiological parameter comprises pulse rate, respiration rate, respiratory effort, and/or oxygen saturation.

16. The system of claim 11 wherein the processor is capable of determining the energy within a moving wedge shaped area of the wavelet scalogram.

17. The system of claim 11 wherein the processor is capable of determining a pulse ridge energy of the wavelet scalogram, wherein the threshold value is based, at least in part, on the determined pulse ridge energy.

18. The system of claim 11 wherein the threshold value is based at least in part upon at least a local wavelet component and a global wavelet component.

19. The system of claim 18 wherein the local wavelet component is derived from the energy within the predefined moving area of the wavelet scalogram over a first time window, and the global wavelet component is derived from a pulse ridge energy over a second time window, wherein the second time window is longer than the first time window.

20. The system of claim 11 wherein the threshold value is based, at least in part, on a running or moving average of the determined energy within the predefined moving area of the wavelet scalogram.

21. A computer-readable medium for use in detecting an artifact in a signal, the computer-readable medium having computer program instructions recorded thereon for:

transforming the signal using a continuous wavelet transform to generate a transformed signal;

generating a wavelet scalogram based, at least in part, on the transformed signal;

determining energy within a predefined moving area of the wavelet scalogram;

comparing the determined energy within the predefined moving area of the wavelet scalogram to a threshold value; and

masking at least one area of artifact in the wavelet scalogram based, at least in part, on the comparison.