System for estimating the actual ECG of a patient during CPR

• US 7,476,206 B2
• Filed: 05/12/2004
• Issued: 01/13/2009
• Est. Priority Date: 10/25/2002
• Status: Expired due to Fees

• Current Assignee: Zoll Circulation Incorporated (Asahi Kasei Corporation)
• Original Assignee: Zoll Circulation Incorporated (Asahi Kasei Corporation)
• Inventors: Palazzolo, James Adam, Berger, Ronald D., Halperin, Henry R., Sherman, Darren R.
• Primary Examiner(s): DEMILLE, DANTON D
• Application Number:
  US10/845,460
• Publication Number:
  US 20040210172A1
• Time in Patent Office: 1,707 Days
• Field of Search: 601 41- 44, 601/DIG.8, 601/DIG.10, 128/901, 600/513, 607/4, 607/5, 607/7
• US Class Current: 601/41
• CPC Class Codes: A61B 5/053 Measuring electrical impedance or conductance of a portion of the body
• CPC Class Codes: A61B 5/0535 Impedance plethysmography for measuring blood flow A61B5/0295
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/339 Displays specially adapted therefor
• 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: A61B 5/7242 using integration
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61H 2201/5007 computer controlled
• CPC Class Codes: A61H 2201/501 connected to external computer devices or networks
• CPC Class Codes: A61H 2201/5012 using the internet
• 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 2201/5084 Acceleration sensors
• CPC Class Codes: A61H 2201/5097 wireless
• CPC Class Codes: A61H 2230/04 Heartbeat characteristics, e.g. E.G.C., blood pressure modulation
• CPC Class Codes: A61H 2230/08 Other bio-electrical signals
• CPC Class Codes: A61H 2230/40 Respiratory characteristics
• 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: A61H 31/008 : Supine patient supports or bases, e.g. improving air-way access to the lungs
• CPC Class Codes: A61M 16/00 : Devices for influencing the respiratory system of patients by gas treatment, e.g. mouth-to-mouth respiration; Tracheal tubes stimulating the respiratory movement by mechanical, pneumatic or electrical means, iron lungs combined with gas breathing means A61H31/00
• CPC Class Codes: A61M 16/0078 : Breathing bags
• CPC Class Codes: A61N 1/39044 : in combination with cardiopulmonary resuscitation [CPR] therapy
• CPC Class Codes: G06F 2218/04 : Denoising
• CPC Class Codes: Y10S 128/901 : Suppression of noise in electric signal
• CPC Class Codes: Y10S 601/08 : Artificial respiration with computer control
• CPC Class Codes: Y10S 601/09 : including biological sensors
• CPC Class Codes: Y10S 601/10 : Artificial respiration combined with non-artificial respiration therapy

Abstract

A method of processing a raw acceleration signal, measured by an accelerometer-based compression monitor, to produce an accurate and precise estimated actual depth of chest compressions. The raw acceleration signal is filtered during integration and then a moving average of past starting points estimates the actual current starting point. An estimated actual peak of the compression is then determined in a similar fashion. The estimated actual starting point is subtracted from the estimated actual peak to calculate the estimated actual depth of chest compressions. In addition, one or more reference sensors (such as an ECG noise sensor) may be used to help establish the starting points of compressions. The reference sensors may be used, either alone or in combination with other signal processing techniques, to enhance the accuracy and precision of the estimated actual depth of compressions.

Claims

1. A system for estimating an actual ECG signal of a patient while performing chest compressions with an automatic chest compressions device, said system comprising:

an ECG sensor capable of measuring an ECG signal of the patient, said ECG sensor producing a measured ECG signal having an actual ECG component and a noise component;

an automatic chest compression device adapted to repeatedly compress the chest of the patient disposed to provide chest compressions to the patient, said chest compression device having a load sensor capable of determining the presence of a chest compression when the load sensed by the load sensor exceeds a predetermined value, said load sensor producing a compression signal corresponding the presence a chest compression;

a signal processing system operable to receive the measured ECG signal and the compression signal, said signal processing system programmed to estimate the noise component of the measured ECG signal with a system identifier by processing the measured ECG signal and the compression signal, combine the measured ECG signal and the estimated noise component of the measured ECG signal, and calculate the estimated actual ECG.

2. The system of claim 1 wherein the load sensor is disposed beneath the patient during compressions.

3. The system of claim 1 wherein the signal processing system comprises a system identifier comprising a moving average filter.

4. The system of claim 1 wherein the signal processing system comprises a system identifier comprising an autoregressive moving average filter.

5. The system of claim 1 wherein the signal processing system comprises a system identifier comprising an autoregressive moving average with truncated derivative filter.

6. The system of claim 1 wherein the signal processing system comprises a system identifier comprising a Kalman filter.

7. The system of claim 1 wherein the signal processing system comprises a system identifier comprising a recursive least squares filter.

8. The system of claim 1 wherein the signal processing system comprises a system identifier comprising a recursive instrumental variable filter.

9. The system of claim 1 wherein the signal processing system comprises a system identifier comprising a recursive prediction error filter.

10. The system of claim 1 wherein the signal processing system comprises a system identifier comprising a recursive pseudolinear regression filter.

11. The system of claim 1 wherein the signal processing system comprises a system identifier comprising a recursive Kalman filter for time-varying systems filter.

12. The system of claim 1 wherein the signal processing system comprises a system identifier comprising a recursive Kalman filter with parametric variation filter.

13. A system for estimating an actual ECG signal of a patient while performing chest compressions with an automatic chest compressions device, said system comprising:

an ECG sensor capable of measuring an ECG signal of the patient, said ECG sensor producing a measured ECG signal having an actual ECG component and a noise component;

an automatic chest compression device adapted to repeatedly compress the chest of the patient disposed to provide chest compressions to the patient, said chest compression device having an encoder capable of determining the presence of a chest compression, said encoder producing a compression signal corresponding the presence a chest compression;

a signal processing system operable to receive the measured ECG signal and the compression signal, said signal processing system programmed to estimate the noise component of the measured ECG signal with a system identifier by processing the measured ECG signal and the compression signal, combine the measured ECG signal and the estimated noise component of the measured ECG signal, and calculate the estimated actual ECG.

14. The system of claim 13 wherein the encoder is an optical encoder.

15. The system of claim 13 wherein the encoder comprises a rotary encoder.

16. The system of claim 13 wherein the signal processing system comprises a system identifier comprising a moving average filter.

17. The system of claim 13 wherein the signal processing system comprises a system identifier comprising an autoregressive moving average filter.

18. The system of claim 13 wherein the signal processing system comprises a system identifier comprising an autoregressive moving average with truncated derivative filter.

19. The system of claim 13 wherein the signal processing system comprises a system identifier comprising a Kalman filter.

20. The system of claim 13 wherein the signal processing system comprises a system identifier comprising a recursive least squares filter.

21. The system of claim 13 wherein the signal processing system comprises a system identifier comprising a recursive instrumental variable filter.

22. The system of claim 13 wherein the signal processing system comprises a system identifier comprising a recursive prediction error filter.

23. The system of claim 13 wherein the signal processing system comprises a system identifier comprising a recursive pseudolinear regression filter.

24. The system of claim 13 wherein the signal processing system comprises a system identifier comprising a recursive Kalman filter for time-varying systems filter.

25. The system of claim 13 wherein the signal processing system comprises a system identifier comprising a recursive Kalman filter with parametric variation filter.

26. A system for estimating an actual ECG signal of a patient while performing chest compressions with an automatic chest compressions device, said system comprising:

an ECG sensor capable of measuring an ECG signal of the patient, said ECG sensor producing a measured ECG signal having an actual ECG component and a noise component;

an automatic chest compression device adapted to repeatedly compress the chest of the patient disposed to provide chest compressions to the patient, said chest compression device having an accelerometer capable of determining the presence of a chest compression, said accelerometer producing a compression signal corresponding the presence a chest compression;

a signal processing system operable to receive the measured ECG signal and the compression signal, said signal processing system programmed to estimate the noise component of the measured ECG signal with a system identifier by processing the measured ECG signal and the compression signal, combine the measured ECG signal and the estimated noise component of the measured ECG signal, and calculate the estimated actual ECG.

27. The system of claim 26 wherein the signal processing system comprises a system identifier comprising a moving average filter.

28. The system of claim 26 wherein the signal processing system comprises a system identifier comprising an autoregressive moving average filter.

29. The system of claim 26 wherein the signal processing system comprises a system identifier comprising an autoregressive moving average with truncated derivative filter.

30. The system of claim 26 wherein the signal processing system comprises a system identifier comprising a Kalman filter.

31. The system of claim 26 wherein the signal processing system comprises a system identifier comprising a recursive least squares filter.

32. The system of claim 26 wherein the signal processing system comprises a system identifier comprising a recursive instrumental variable filter.

33. The system of claim 26 wherein the signal processing system comprises a system identifier comprising a recursive prediction error filter.

34. The system of claim 26 wherein the signal processing system comprises a system identifier comprising a recursive pseudolinear regression filter.

35. The system of claim 26 wherein the signal processing system comprises a system identifier comprising a recursive Kalman filter for time-varying systems filter.

36. The system of claim 26 wherein the signal processing system comprises a system identifier comprising a recursive Kalman filter with parametric variation filter.