Using chest velocity to process physiological signals to remove chest compression artifacts

• US 9,521,978 B2
• Filed: 10/10/2014
• Issued: 12/20/2016
• Est. Priority Date: 11/06/2003
• Status: Expired due to Term

• Current Assignee: Zoll Medical Corporation (Asahi Kasei Corporation)
• Original Assignee: Zoll Medical Corporation (Asahi Kasei Corporation)
• Inventors: Freeman, Gary A., Tan, Qing, Geheb, Frederick J.
• Primary Examiner(s): Gedeon, Brian T
• Application Number:
  US14/512,167
• Publication Number:
  US 20150031972A1
• Time in Patent Office: 802 Days
• Field of Search: None
• US Class Current: 1/1
• 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 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• 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 5/346 Analysis of electrocardiograms
• CPC Class Codes: A61B 5/361 Detecting fibrillation
• CPC Class Codes: A61B 5/4836 Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61B 5/4848 Monitoring or testing the effects of treatment, e.g. of medication
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: A61B 5/721 using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured
• CPC Class Codes: A61H 2201/5043 Displays
• CPC Class Codes: A61H 2201/5048 Audio interfaces, e.g. voice or music controlled
• CPC Class Codes: A61H 2201/5058 Sensors or detectors
• CPC Class Codes: A61H 2201/5079 Velocity sensors
• CPC Class Codes: A61H 2201/5084 Acceleration sensors
• CPC Class Codes: A61H 2230/04 Heartbeat characteristics, e.g. E.G.C., blood pressure modulation
• CPC Class Codes: A61H 31/005 with feedback for the user
• CPC Class Codes: A61H 31/006 Power driven
• CPC Class Codes: A61H 31/007 Manual driven
• CPC Class Codes: A61N 1/046 Specially adapted for shock therapy, e.g. defibrillation
• CPC Class Codes: A61N 1/0492 : Patch electrodes A61N1/0412, A61N1/0428 take precedence
• CPC Class Codes: A61N 1/3925 : Monitoring; Protecting
• CPC Class Codes: A61N 1/3987 : characterised by the timing or triggering of the shock
• CPC Class Codes: A61N 1/3993 : User interfaces for automatic external defibrillators

Abstract

A method of analyzing a physiological (e.g., an ECG) signal during application of chest compressions. The method includes acquiring a physiological signal during application of chest compressions; acquiring the output of a sensor from which information on the velocity of chest compressions can be determined; and using the information on the velocity to reduce at least one signal artifact in the physiological signal resulting from the chest compressions.

Claims

1. A method of analyzing a physiological signal during application of chest compressions, the method comprising:

acquiring a physiological signal during application of chest compressions;

acquiring the output of a sensor from which information on the velocity of chest compressions can be determined;

using the information on the velocity to reduce at least one signal artifact in the physiological signal resulting from the chest compressions; and

using a ventricular fibrillation detection algorithm for processing the physiological signal with reduced artifact to estimate whether a ventricular fibrillation is present,

wherein using the information on the velocity to reduce at least one signal artifact in the physiological signal comprises using an adaptive filter that is adjusted to remove chest compression artifacts,

wherein a difference signal is produced, the difference signal being representative of the difference between the physiological signal fed into the adaptive filter and the physiological signal after artifact reduction by the adaptive filter,

wherein the difference signal provides a measure of the amount of artifact in the physiological signal, and

further comprising the step of using the difference signal to modify the subsequent processing of the physiological signal,

wherein, if the difference signal indicates that the amount of artifact exceeds a first threshold, the ventricular fibrillation detection algorithm is modified to make it more resistant to being influenced by the artifact.

2. The method of claim 1 wherein, if the difference signal indicates that the amount of artifact exceeds a second threshold higher than the first threshold, use of the ventricular defibrillation detection algorithm is suspended.

3. A method of analyzing a physiological signal during application of chest compressions, the method comprising:

acquiring a physiological signal during application of chest compressions;

acquiring the output of a sensor from which information on the velocity of chest compressions can be determined; and

using the information on the velocity to reduce at least one signal artifact in the physiological signal resulting from the chest compressions,

wherein using the information on the velocity to reduce at least one signal artifact in the physiological signal comprises using an adaptive filter that is adjusted to remove chest compression artifacts,

wherein a difference signal is produced, the difference signal being representative of the difference between the physiological signal fed into the adaptive filter and the physiological signal after artifact reduction by the adaptive filter, and

wherein the adaptive filter comprises the capability of being automatically reset when the difference signal exceeds a threshold.

4. A method of analyzing a physiological signal during application of chest compressions, the method comprising:

acquiring a physiological signal during application of chest compressions;

acquiring the output of a sensor from which information on the velocity of chest compressions can be determined; and

using the information on the velocity to reduce at least one signal artifact in the physiological signal resulting from the chest compressions,

wherein using the information on the velocity to reduce at least one signal artifact in the physiological signal comprises using an adaptive filter that is adjusted to remove chest compression artifacts, and

wherein the adaptive filter comprises the capability of dynamically changing a step size and thus improving a relationship of convergence and stability of the filter.

5. A method of analyzing a physiological signal during application of chest compressions, the method comprising:

acquiring a physiological signal during application of chest compressions;

acquiring the output of a sensor from which information on the velocity of chest compressions can be determined; and

using the information on the velocity to reduce at least one signal artifact in the physiological signal resulting from the chest compressions,

wherein using the information on the velocity to reduce at least one signal artifact in the physiological signal comprises using an adaptive filter that is adjusted to remove chest compression artifacts,

further comprising a ventricular fibrillation detection algorithm for processing the physiological signal with reduced artifact to estimate whether a ventricular fibrillation is present,

further comprising a preprocessing step that detects when chest compressions are applied and automatically initiates the adaptive filter,

further comprising a time-aligning process performed on the physiological and velocity signals, wherein the time aligning process aligns the two signals relative to the compressions, and

further comprising adaptive filtering of the output of the time aligning process, wherein the adaptive filtering reduces the error between the physiological and velocity signals.

6. A method of analyzing a physiological signal during application of chest compressions, the method comprising:

acquiring a physiological signal during application of chest compressions;

acquiring the output of a sensor from which information on the velocity of chest compressions can be determined; and

using the information on the velocity to reduce at least one signal artifact in the physiological signal resulting from the chest compressions,

wherein using the information on the velocity to reduce at least one signal artifact in the physiological signal comprises using an adaptive filter that is adjusted to remove chest compression artifacts and

wherein the adaptive filter employs adaptive equalization.

7. The method of claim 6 further comprising a ventricular fibrillation detection algorithm for processing the physiological signal with reduced artifact to estimate whether a ventricular fibrillation is present.

8. The method of claim 7 further comprising a preprocessing step that detects when chest compressions are applied and automatically initiates the adaptive filter.

9. The method of claim 8 wherein the physiological signal is an ICG signal.

10. The method of claim 8 wherein the physiological signal is a pulse oximetry signal.

11. The method of claim 8 wherein the sensor is a velocity sensor, and the information on the velocity is determined from the velocity sensor.

12. The method of claim 8 wherein the sensor is an accelerometer, and the information on the velocity is determined from integration of the output of the accelerometer.

13. The method of claim 8 wherein using the information on the velocity to reduce at least one signal artifact in the physiological signal comprises time aligning the physiological signal with the velocity.

14. The method of claim 8 further comprising enabling delivery of a defibrillation shock if the algorithm estimates that ventricular fibrillation is present.

15. The method of claim 8 further comprising a time-aligning process performed on the physiological and velocity signals, wherein the time aligning process aligns the two signals relative to the compressions.

16. The method of claim 15 further comprising adaptive filtering of the output of the time aligning process, wherein the adaptive filtering reduces the error between the physiological and velocity signals.

17. The method of claim 8 wherein the physiological signal is an ECG signal.

18. The method of claim 8 wherein the physiological signal is an IPG signal.

19. The method of claim 6 wherein a difference signal is produced, the difference signal being representative of the difference between the physiological signal fed into the adaptive filter and the physiological signal after artifact reduction by the adaptive filter.

20. The method of claim 19 wherein the difference signal provides a measure of the amount of artifact in the physiological signal.

21. The method of claim 20 further comprising the step of using the difference signal to modify the subsequent processing of the physiological signal.

22. The method of claim 21 wherein, if the difference signal indicates that the amount of artifact exceeds a first threshold, the ventricular fibrillation detection algorithm is modified to make it more resistant to being influenced by the artifact.

23. The method of claim 22 wherein, if the difference signal indicates that the amount of artifact exceeds a second threshold higher than the first threshold, use of the ventricular defibrillation detection algorithm is suspended.

24. The method of claim 21 wherein spectral analysis is performed on the difference signal, and adjustments are made to filtering of the physiological signal based on the outcome of the spectral analysis.

25. The method of claim 6 wherein the velocity signal undergoes a normalization pre-processing prior to being fed to an adaptive filter.

26. The method of claim 6 wherein the adaptive filter comprises an FIR filter.

27. The method of claim 26 wherein the adaptive filter comprises a zero-th order filter.

28. The method of claim 6 wherein the adaptive filter comprises coefficients that are dynamically controlled by an estimate of the physiological signal.

29. The method of claim 6 wherein the adaptive filter comprises the capability of being automatically reset when the difference between the filter output and the measured physiological signal is beyond a threshold.

30. The method of claim 29 wherein the automatic reset comprises the capability of dynamically changing the step size and thus improving the relationship of convergence and stability of the filter.

31. The method of claim 6 wherein the adaptive filter comprises a Kalman filter.