Signal Processing Warping Technique

• US 20110071378A1
• Filed: 09/13/2010
• Published: 03/24/2011
• Est. Priority Date: 09/24/2009
• Status: Active Grant

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: Nellcor Puritan Bennett LLC (Medtronic Plc)
• Inventors: Peters, Daniel Jon, McKenna, Edward M.
• Granted Patent: US 8,840,562 B2
• Time in Patent Office: Days
• US Class Current: 600/364
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/6816 Ear lobe
• 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 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00

Abstract

Methods and systems are provided for using time-frequency warping to analyze a physiological signal. One embodiment includes applying a warping operator to the physiological signal based on the energy density of the signal. The warped physiological signal may be analyzed to determine whether non-physiological signal components are present. Further, the same warping operator may be applied to signal quality indicators, and the warped physiological signal may be analyzed based on the warped signal quality indicators. Non-physiological signal components, or types of non-physiological noise sources, may be identified based on a comparison of the physiological signal with the signal quality indicators. Non-physiological signal components may also be identified based on a neural network of known noise functions. In some embodiments, the non-physiological signal components may be removed to increase accuracy in estimating physiological parameters.

Claims

1. A method for processing a physiological signal, comprising the acts of:

warping a time-frequency representation of the physiological signal with a warping function to produce a warped physiological signal; and

identifying a non-physiological signal component based on the warped physiological signal.

2. The method, as set forth in claim 1, comprising selecting the warping function based on an energy density of the physiological signal.

3. The method, as set forth in claim 1, comprising warping a signal quality indicator with the warping function, and wherein identifying a non-physiological signal component is based on an analysis of the warped physiological signal and a warped signal quality indicator.

4. The method, as set forth in claim 3, wherein the signal quality indicator comprises one or more signals derived from known physiological and non-physiological signal characteristics.

5. The method, as set forth in claim 3, wherein the signal quality indicator comprises one or more signals indicative optical interference, undesired light modulation, physical movement of a patient, or improper sensor placement.

6. The method, as set forth in claim 1, comprising removing the non-physiological signal component from the physiological signal.

7. The method, as set forth in claim 1, comprising indicating the presence of the non-physiological signal on a pulse oximeter measuring the physiological signal.

8. The method, as set forth in claim 1, comprising indicating a source of the non-physiological signal on a pulse oximeter measuring the physiological signal.

9. The method, as set forth in claim 1, comprising using the non-physiological signal in a neural network and identifying future occurrences of the non-physiological signal based on the neural network.

10. A method for using time and frequency warping to analyze a physiological signal, comprising the acts of:

warping the physiological signal with a warping function;

warping a signal quality indicator with the warping function;

analyzing the warped physiological signal and the warped signal quality indicator; and

identifying a non-physiological signal component based on the analysis.

11. The method, as set forth in claim 10, wherein analyzing the warped physiological signal and the warped signal quality indicator comprises analyzing the two signals in a common time scale.

12. The method, as set forth in claim 11, wherein analyzing the warped physiological signal and the warped signal quality indicator comprises cross-correlating the two signals.

13. The method, as set forth in claim 12, wherein identifying the non-physiological signal component comprises determining whether a cross-correlation of the two signals indicates a non-physiological signal component.

14. The method, as set forth in claim 13, wherein a non-physiological signal component is identifiable based on whether a portion of the cross-correlation surpasses a threshold.

15. The method, as set forth in claim 10, wherein identifying the non-physiological signal component comprises comparing a scalogram of the warped physiological signal with a scalogram of the warped signal quality indicator.

21. The pulse oximetry system of claim 10, comprising a display on which the data processing circuitry displays an indication of the type or presence of the identified non-physiological signal components.

16. A pulse oximetry system, comprising:

data processing circuitry capable of applying time-frequency warping to a physiological signal, analyzing the time-frequency warped physiological signal, and identifying non-physiological signal components based on the analysis of the time-frequency warped physiological signal.

17. The pulse oximetry system of claim 16, wherein the data processing circuitry capable of applying time-frequency warping to a physiological signal warps the physiological signal with a warp operator.

18. The pulse oximetry system of claim 17, wherein the data processing circuitry is further capable of warping a signal quality indicator with the warp operator.

19. The pulse oximetry system of claim 18, wherein analyzing the time-frequency warped physiological signal comprises analyzing the warped physiological signal based on a warped signal quality indicator.

20. The pulse oximetry system of claim 16, wherein applying time-frequency warping to the physiological signal is based on an energy density of the physiological signal.