Photoplethysmograph Filtering Using Empirical Mode Decomposition

• US 20110245628A1
• Filed: 03/31/2010
• Published: 10/06/2011
• Est. Priority Date: 03/31/2010
• Status: Abandoned Application

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: Nellcor Puritan Bennett LLC (Medtronic Plc)
• Inventors: Peters, Daniel, McKenna, Edward M., Li, Youzhi, Baker, Clark R. JR.
• Application Number:
  US12/751,274
• Publication Number:
  US 20110245628A1
• Time in Patent Office: Days
• US Class Current: 600/301
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• 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 5/0261 using optical means, e.g. infrared light
• 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

Abstract

Present embodiments relate to systems, methods, and devices for decomposing a physiological signal of a patient using empirical mode decomposition (EMD). In one embodiment, the EMD algorithm may involve identifying a frequency component, referred to as an intrinsic mode function, in the physiological signal. The physiological signal may be decomposed into one or more intrinsic mode functions through multiple iterations of the EMD algorithm. Each subsequent mode function may have a different frequency component of the original physiological signal input into the EMD algorithm. In some embodiments, each mode function may be further analyzed and/or processed to determine various physiological data corresponding to blood flow in the patient.

Claims

1. A method comprising:

applying an empirical mode decomposition (EMD) algorithm on a physiological signal to produce one or more intrinsic mode functions, wherein the physiological signal corresponds to blood flow in a patient; and

determining one or more physiological parameters based on the one or more intrinsic mode functions.

2. The method of claim 1, wherein applying the EMD algorithm comprises:

identifying a maxima and a minima of the physiological signal;

calculating an upper envelope and a lower envelope based on the maxima and the minima; and

subtracting a mean of the upper envelope and the lower envelope from the physiological signal to produce a first mode of the one or more intrinsic mode functions.

3. The method of claim 2, wherein determining one or more physiological parameters comprises determining a pulse rate of the patient based on the first mode.

4. The method of claim 2, comprising:

subtracting the first mode from the physiological signal to produce a residual;

identifying a maxima and a minima of the residual;

calculating an upper envelope and a lower envelope of the residual based on the maxima and the minima of the residual; and

subtracting a mean of the upper envelope and the lower envelope of the residual to produce a second mode of the one or more intrinsic functions.

5. The method of claim 4, wherein determining one or more physiological parameters comprises determining a heart arrhythmia or a respiratory rate of the patient based on the second mode.

6. The method of claim 1, comprising processing the one or more intrinsic mode functions by performing one or more of multiplexing, amplifying, digitizing, filtering, normalizing, resealing, and transforming the one or more intrinsic mode functions.

7. The method of claim 1, wherein determining the one or more physiological parameters comprises computing a ratio of pulse amplitudes by using one or more of linear regression techniques, linear combination techniques, multivariate analysis, principal component analysis, and independent component analysis.

8. The method of claim 1, wherein the one or more physiological parameters comprises one or more of arterial or venous oxygen saturation, pulse rate, continuous non-invasive blood pressure, pulse transit time, respiratory rate or effort, pulse amplitude, tissue perfusion, hypoxia, hyperoxia, bradycardia, tachycardia, arrhythmia, central or obstructive apnea, hypopnea, Cheyne-Stokes syndrome, hypovolemia, and sympathetic nervous activity.

9. A method of determining physiological information of a patient comprising:

identifying extrema in an input signal, wherein the input signal comprises a portion of a physiological signal of the patient;

calculating input signal envelopes based on the extrema of the input signal;

subtracting a mean of the input signal envelopes from the input signal to produce a first mode function;

subtracting the first mode function from the input signal to produce a residual signal;

identifying extrema in the residual signal;

calculating residual signal envelopes based on the extrema of the residual signal;

subtracting a mean of the residual signal envelopes from the residual signal to produce a second mode function; and

determining physiological information of the patient based on one or more of the first mode function and the second mode function.

10. The method of claim 9, wherein the input signal comprises a time window of samples from the physiological signal.

11. The method of claim 10, wherein the method is performed on a subsequent time window of samples from the physiological signal, wherein the subsequent time window overlaps with the time window.

12. The method of claim 9, wherein identifying the extrema in the input signal comprises ignoring samples in the input signal corresponding to a dicrotic notch of the patient.

13. The method of claim 9, wherein identifying the extrema in the input signal and identifying the extrema in the residual signal comprises ignoring samples not relevant to the physiological information to be determined by the first mode function and the second mode function.

14. The method of claim 9, wherein a variance of the second mode function is compared with a variance of the first mode function, and wherein an additional iteration is performed to produce a refined second mode function if the variance of the second mode function is less than the variance of the first mode function, wherein the additional iteration comprises:

subtracting the second mode function from the residual signal to produce a second residual;

identifying extrema in the second residual;

calculating second residual envelopes based on the extrema of the second residual; and

subtracting a mean of the second residual envelopes from the second residual to produce a refined second mode function.

15. The method of claim 9, comprising:

determining whether to refine the first mode function based on a comparison of statistical measures of the first mode function with threshold statistical measures; and

performing one or more iterations to produce a refined first mode function, wherein the one or more iterations each comprise;

subtracting the first mode function from the input signal to produce an unrefined residual signal;

identifying extrema in the unrefined residual signal;

calculating unrefined residual signal envelopes based on the extrema of the unrefined residual signal; and

subtracting a mean of the unrefined residual signal envelopes from the unrefined residual signal to produce a refined first mode function.

16. The method of claim 15, wherein the statistical measures comprise one or more of a variance, a kurtoses, a skewness, a number of minima, a number of maxima, a number of zero crossings, and a number of cycles of the first mode function.

17. The method of claim 9, comprising calculating subsequent mode functions until a number of cycles of a mode function is below a threshold.

18. The method of claim 9, wherein determining physiological information of the patient comprises comparing one or more of the first mode function, the second mode function, and the input signal.

19. A system for determining physiological information of a patient, the system comprising:

a sensor configured to detect a physiological signal from the patient;

a patient monitor coupled to the sensor, wherein the patient monitor comprises;

a processor configured to apply an empirical mode decomposition (EMD) algorithm on the physiological signal to produce one or more intrinsic mode functions; and

a processor configured to process the one or more intrinsic mode functions to determine one or more physiological parameters.

20. The system of claim 19, wherein the processor is configured to apply the EMD algorithm iteratively on the physiological signal to produce subsequent intrinsic mode functions.

21. The system of claim 19, wherein the processor is configured to iteratively apply the EMD algorithm on the physiological signal until the one or more intrinsic mode functions represent substantially all physiological oscillations in the physiological signal.

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

calculate statistical measures of the one or more intrinsic mode functions;

compare the calculated statistical measures with threshold statistical measures;

determine whether each of the one or more intrinsic mode functions is sufficiently refined based on the comparison; and

iteratively apply portions of the EMD algorithm on each of the one or more intrinsic mode functions until each of the one or more intrinsic mode functions is determined to be sufficiently refined.

23. The system of claim 19, wherein the processor is configured to compare a first mode of the one or more intrinsic mode functions with a second mode of the one or more intrinsic mode functions, and wherein the processor is configured to produce a third mode of the one or more intrinsic mode functions based on a comparison of the first mode and the second mode.