Elsevier

Resuscitation

Volume 75, Issue 1, October 2007, Pages 145-152
Resuscitation

Experimental paper
Rhythm discrimination during uninterrupted CPR using motion artifact reduction system

https://doi.org/10.1016/j.resuscitation.2007.03.007Get rights and content

Summary

Background

Due to motion artifact in the ECG caused by chest compressions automatic external defibrillators (AEDs) have difficulty recognizing ventricular fibrillation (VF) during cardiopulmonary resuscitation (CPR). Frequent interruption of CPR is required for artifact-free ECG interpretation, but these interruptions reduce the efficacy of CPR. We developed a motion artifact reduction system (MARS), based on adaptive noise cancellation techniques, for use during CPR. We hypothesized that this system would allow for automated rhythm discrimination during uninterrupted CPR.

Methods and results

Thirteen swine underwent CPR during normal sinus rhythm (NSR) and repeated inductions of VF and asystole, using an automated device that uses a load-distributing band to compress the anterior chest. A single ECG lead and the instantaneous compression force signal were sampled during continuous CPR and fed to MARS, which in turn provided a filtered ECG signal in which artifacts that correlated with compression force were suppressed. The filtered and unfiltered ECGs were then fed simultaneously, and in real time, to three pairs of defibrillators with rhythm discrimination functions. During CPR, non-shockable rhythms were correctly classified by the defibrillators in 59 of 63 instances using the raw ECG, and 60 of 63 instances using the MARS-filtered ECG (p = N.S.). During CPR, VF was correctly classified in 35 of 222 attempts using the raw ECG, and in 310 of 318 cases using the MARS-filtered ECG (p < 0.001). As control, when CPR was not applied, all rhythms were correctly identified by each defibrillator using either the raw ECG or the filtered ECG.

Conclusions

Motion artifact reduction by adaptive noise cancellation allows for recognition of VF during uninterrupted automated CPR, while this is rarely possible based on the raw ECG. Incorporation of this signal processing strategy may obviate the need for interruptions in chest compression and thus enhance CPR efficacy.

Introduction

Chest compressions represent an essential component of cardiopulmonary resuscitation (CPR), but the compressions often render the ECG uninterpretable due to associated motion artifact. Since management decisions regarding administration of medications and application of defibrillation shocks are predicated by the electrocardiographic rhythm, chest compressions are interrupted during CPR, often repeatedly and for many seconds at a time, to allow for acquisition of uncorrupted ECGs. However, interruptions in chest compressions reduce the hemodynamic benefit and likelihood of survival from CPR.1, 2 Interruption of chest compressions is also required when using automatic external defibrillators (AEDs). These devices instruct the operator to discontinue compressions so that the ECG can be analyzed, delaying appropriate therapy and limiting the time for chest compressions to roughly 40% of CPR time.3, 4, 5, 6

We hypothesized that artifacts in the ECG related to chest compressions could be removed using adaptive noise cancellation techniques, enabling automated rhythm discrimination by standard AED algorithms, during uninterrupted CPR. We tested this hypothesis by processing in real time the ECG obtained from anesthetized swine undergoing CPR using a load-distributing band to compress the anterior chest, and feeding the filtered ECG to three different commercial AED or equivalent devices for rhythm analysis. The unfiltered ECG was fed simultaneously to three identical AED devices to serve as control.

Section snippets

Animal preparation

Thirteen swine (20–25 kg) of either sex received ketamine 22 mg/kg intramuscularly. After tracheal intubation and mechanical ventilation, anesthesia was maintained with isoflurane (1–2.5%) in 100% oxygen, and minute ventilation was titrated to achieve an end-tidal CO2 between 35 and 45 mmHg. From a jugular cutdown, a pacing catheter was placed into the right ventricle. The animals were prepared by shaving and scrubbing the chest with alcohol. Adult defibrillation pads (Quick Combo, Medtronic) were

Recorded waveforms

Examples of measured and calculated waveforms obtained during NSR and VF are shown in Figure 3, Figure 4, respectively. In these examples, the instantaneous force signal measured from the automatic compression device and the raw surface ECG are shown in the top two traces. The part of the raw ECG signal that the MARS system determined to represent artifact, based on correlation with the force signal, is shown in the third tracing, and the predicted “true” ECG, calculated as the difference

Main findings

The main findings of this study are that (1) motion artifacts in the ECG introduced by automated CPR can be greatly suppressed using adaptive noise cancellation when a reference signal related to compression force is available, (2) MARS allows for appropriate automated recognition of VF during uninterrupted CPR, while this is rarely possible based on the raw ECG, (3) MARS does not introduce artifacts that would lead to misclassification of NSR or asystole during CPR, and (4) MARS does not

Conclusion

Motion artifacts in the ECG caused by chest compressions during automated CPR can be effectively suppressed using adaptive noise cancellation techniques. With this strategy, automated arrhythmia detection is feasible during uninterrupted CPR. Clinical testing of this system should be pursued to determine whether it leads to improved survival with CPR.

Conflict of interest

Drs. Berger and Halperin are paid consultants of ZOLL Medical Corp. The terms of this arrangement are being managed by the Johns Hopkins University in accordance with its conflict of interest policies. Mr. Palazzolo is an employee of ZOLL Medical Corp.

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    A Spanish translated version of the summary of this article appears as Appendix in the final online version at 10.1016/j.resuscitation.2007.03.007.

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