Reducing CPR artefacts in ventricular fibrillation in vitro

Langhelle, Audun; Eftestøl, Trygve; Myklebust, Helge; Eriksen, Morten; Holten, Bjørn Terje; Steen, Petter Andreas

doi:10.1016/s0300-9572(00)00259-8

Cited by 52 publications

(39 citation statements)

References 9 publications

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“…However, their VF signal model is more realistic than our white noise assumption. The research group of Eftestol, Husoy et al [5], [16], [17] applies an adaptive matching pursuit-like algorithm using multiple reference signals. Their CPR estimates are given by adaptively optimized linear combinations of past and current reference signal values, whereas our CPR estimates also include future values.…”

Section: Discussionmentioning

confidence: 99%

“…• The Norwegian research group of Eftestol, Husoy et al [5], [16], [17] applies an adaptive filtering approach using additional reference signals (thoracic impedance, compression depth, etc. ), which correlate with the CPR artifact signal.…”

Section: B Previous Workmentioning

confidence: 99%

“…The international guidelines 2005 emphasize high-quality CPR [4]: Rescuers should push hard, push fast, allow full chest recoil, minimize interruptions in compressions, and defibrillate promptly when appropriate. Yet, during CPR, chest compressions and ventilations cause artifacts in the ECG [5]. In order for the rhythm detection algorithms of automatic external defibrillators to work properly, a so-called "hands-off interval" is required, where CPR stops and ECG is artifact free.…”

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confidence: 99%

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Removal of CPR Artifacts From the Ventricular Fibrillation ECG by Adaptive Regression on Lagged Reference Signals

Rheinberger

Steinberger

Unterkofler

et al. 2008

IEEE Trans. Biomed. Eng.

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Section: Discussionmentioning

confidence: 99%

Section: B Previous Workmentioning

confidence: 99%

mentioning

confidence: 99%

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Removal of CPR Artifacts From the Ventricular Fibrillation ECG by Adaptive Regression on Lagged Reference Signals

Rheinberger

Steinberger

Unterkofler

et al. 2008

IEEE Trans. Biomed. Eng.

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“…For this purpose, we used a graphical user interface showing the ECG tracings and impedance measurements at the same time. Artifacts in the ECG and changes in the impedance tracings induced by CPR 16 were used to determine when it was provided. We were able to identify and extract 267 paired pre-CPR and post-CPR VF waveforms without CPR-induced artifacts ( Figure 2) for further analysis from 77 of the 105 patients.…”

Section: Data Collectionmentioning

confidence: 99%

Effects of Cardiopulmonary Resuscitation on Predictors of Ventricular Fibrillation Defibrillation Success During Out-of-Hospital Cardiac Arrest

2004

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Background-Early defibrillation is considered the most important factor for restoring spontaneous circulation in cardiac arrest patients with ventricular fibrillation. Recent studies have shown that, after prolonged ventricular fibrillation, the rates of return of spontaneous circulation (ROSC) and survival are improved if defibrillation is delayed so that CPR can be given first. To examine whether CPR improves myocardial readiness for defibrillation, we analyzed whether CPR causes changes in predictors of defibrillation success calculated from the ventricular fibrillation waveform. Methods and Results-ECG recordings were retrieved for 105 patients from an original study of 200 patients receiving CPR or defibrillation first. Altogether, 267 CPR sequences from 77 patients were identified on which the effect of CPR could be evaluated. Five predictors of ROSC (spectral flatness measure, energy, centroid frequency, amplitude spectrum relationship, and estimated probability of ROSC) were determined from a spectral analysis of the ventricular fibrillation waveform immediately before and immediately after each of the 267 sequences. CPR increased spectral flatness measure, centroid frequency, and amplitude spectrum relationship (PϽ0. 05, PϽ0.001, PϽ0.01). In an analysis of the effect of the duration of CPR, the probability of ROSC and amplitude spectrum relationship showed a positive change for CPR sequences lasting Ͼ3 minutes (PϽ0.001, PϽ0.05). Conclusions-During

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“…More advanced studies [8][9][10] have introduced a human model for the VF signals, maintaining a porcine model for the CPR artifacts. In this case, there is a remarkable overlapping between both the artifact and the ECG signal spectral distribution.…”

Section: Introductionmentioning

confidence: 99%

Ventricular fibrillation detection in ventricular fibrillation signals corrupted by cardiopulmonary resuscitation artifact

Ruiz

Aramendi

Gauna

et al. 2003

Computers in Cardiology, 2003

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Reducing CPR artefacts in ventricular fibrillation in vitro

Cited by 52 publications

References 9 publications

Removal of CPR Artifacts From the Ventricular Fibrillation ECG by Adaptive Regression on Lagged Reference Signals

Removal of CPR Artifacts From the Ventricular Fibrillation ECG by Adaptive Regression on Lagged Reference Signals

Effects of Cardiopulmonary Resuscitation on Predictors of Ventricular Fibrillation Defibrillation Success During Out-of-Hospital Cardiac Arrest

Ventricular fibrillation detection in ventricular fibrillation signals corrupted by cardiopulmonary resuscitation artifact

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