US2009112135A1PendingUtilityA1

Method of Estimating the Actual ECG of a Patient During CPR

Assignee: ZOLL CIRCULATION INCPriority: Oct 25, 2002Filed: Jan 7, 2009Published: Apr 30, 2009
Est. expiryOct 25, 2022(expired)· nominal 20-yr term from priority
G06F 2218/04A61N 1/39044Y10S128/901A61H 2201/5007A61H 2201/5043A61B 5/7242A61B 5/721A61B 5/053Y10S601/10A61H 2230/08A61H 31/007A61H 2201/5084Y10S601/08A61M 16/00A61H 2201/501A61H 2201/5048A61H 31/005A61H 31/006A61H 2201/5012A61B 5/0535A61H 2230/04A61H 2201/5097A61H 31/008A61H 2230/40Y10S601/09A61H 2201/5058A61B 5/725A61M 16/0078A61B 5/316A61B 5/346
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Claims

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

exact text as granted — not AI-modified
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 using one or more filters selected from the group consisting of autoregressive moving average with truncated derivative filter, Kalman filter, recursive least squares filter, recursive instrumental variable filter, recursive prediction error filter, recursive pseudolinear regression filter, recursive Kalman filter for time-varying systems filter, recursive Kalman filter with parametric variation filter, combine the measured ECG signal and the estimated noise component of the measured ECG signal, and calculate the estimated actual ECG.   
   
   
       2 . 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 using one or more filters selected from the group consisting of autoregressive moving average with truncated derivative filter, Kalman filter, recursive least squares filter, recursive instrumental variable filter, recursive prediction error filter, recursive pseudolinear regression filter, recursive Kalman filter for time-varying systems filter, recursive Kalman filter with parametric variation filter, combine the measured ECG signal and the estimated noise component of the measured ECG signal, combine the measured ECG signal and the estimated noise component of the measured ECG signal, and calculate the estimated actual ECG.   
   
   
       3 . 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 using one or more filters selected from the group consisting of autoregressive moving average with truncated derivative filter, Kalman filter, recursive least squares filter, recursive instrumental variable filter, recursive prediction error filter, recursive pseudolinear regression filter, recursive Kalman filter for time-varying systems filter, recursive Kalman filter with parametric variation filter, combine the measured ECG signal and the estimated noise component of the measured ECG signal, combine the measured ECG signal and the estimated noise component of the measured ECG signal, and calculate the estimated actual ECG.

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