CPR artifact removal from human ECG using optimal multichannel filtering

The purpose of this study was to assess whether the artifacts presented by precordial compressions during cardiopulmonary resuscitation could be removed from the human electrocardiogram (ECG) using a filtering approach. This would allow analysis and defibrillator charging during ongoing precordial compressions yielding a very important clinical improvement to the treatment of cardiac arrest patients. In this investigation the authors started with noise-free human ECGs with ventricular fibrillation (VF) and ventricular tachycardia (VT) records. To simulate a realistic resuscitation situation, they added a weighted artifact signal to the human ECG, where the weight factor was chosen to provide the desired signal-to-noise ratio (SNR) level. As artifact signals the authors used ECGs recorded from animals in asystole during precordial compressions at rates 60, 90, and 120 compressions/min. The compression depth and the thorax impedance was also recorded. In a real-life situation such reference signals are available and, using an adaptive multichannel Wiener filter, the authors construct an estimate of the artifact signal, which subsequently can be subtracted from the noisy human ECG signal. The success of the proposed method is demonstrated through graphic examples, SNR, and rhythm classification evaluations.

[1]  T. Aufderheide,et al.  Prehospital experience with defibrillation of coarse ventricular fibrillation: a ten-year review. , 1990, Annals of emergency medicine.

[2]  J. Ornato,et al.  Guidelines for cardiopulmonary resuscitation and emergency cardiac care, V: Pediatric basic life support , 1992 .

[3]  M. Copass,et al.  Improved neurologic recovery and survival after early defibrillation. , 1984, Circulation.

[4]  G A Ewy,et al.  Depletion of myocardial adenosine triphosphate during prolonged untreated ventricular fibrillation: effect on defibrillation success. , 1990, Resuscitation.

[5]  I. Stiell,et al.  Modifiable factors associated with improved cardiac arrest survival in a multicenter basic life support/defibrillation system: OPALS Study Phase I results. Ontario Prehospital Advanced Life Support. , 1999, Annals of emergency medicine.

[6]  P A Naess,et al.  Improved haemodynamics with increased compression-decompression rates during ACD-CPR in pigs. , 1998, Resuscitation.

[7]  Wanchun Tang,et al.  Ventricular fibrillation voltage as a monitor of the effectiveness of cardiopulmonary resuscitation. , 1994, The Journal of laboratory and clinical medicine.

[8]  M. Copass,et al.  Influence of cardiopulmonary resuscitation prior to defibrillation in patients with out-of-hospital ventricular fibrillation , 1999, JAMA.

[9]  C W Otto,et al.  A study of chest compression rates during cardiopulmonary resuscitation in humans. The importance of rate-directed chest compressions. , 1992, Archives of internal medicine.

[10]  A. Hallstrom,et al.  Predicting survival from out-of-hospital cardiac arrest: a graphic model. , 1993, Annals of emergency medicine.

[11]  Thomas D. Lyster,et al.  Treatment of out-of-hospital cardiac arrest with a low-energy impedance-compensating biphasic waveform automatic external defibrillator. The LIFE Investigators. , 1998, Biomedical instrumentation & technology.

[12]  S M Cobbe,et al.  Performance of an established system of first responder out-of-hospital defibrillation. The results of the second year of the Heartstart Scotland Project in the 'Utstein Style'. , 1993, Resuscitation.

[13]  C Robertson,et al.  The 1998 European Resuscitation Council guidelines for adult advanced life support: A statement from the Working Group on Advanced Life Support, and approved by the executive committee. , 1998, Resuscitation.

[14]  P. Steen,et al.  Quality assessment of defribrillation and advanced life support using data from the medical control module of the defibrillator. , 1999, Resuscitation.

[15]  John G. Proakis,et al.  Digital Signal Processing: Principles, Algorithms, and Applications , 1992 .

[16]  M. Weil,et al.  Electrocardiographic prediction of the success of cardiac resuscitation. , 1999, Critical care medicine.

[17]  P A Naess,et al.  Effect of different compression--decompression cycles on haemodynamics during ACD-CPR in pigs. , 1998, Resuscitation.

[18]  Peter No,et al.  Digital Coding of Waveforms , 1986 .

[19]  J D Michenfelder,et al.  The Effects of Anesthesia and Hypothermia on Canine Cerebral ATP and Lactate during Anoxia Produced by Decapitation , 1970, Anesthesiology.

[20]  K. Lindner,et al.  Spectral analysis of ventricular fibrillation and closed-chest cardiopulmonary resuscitation. , 1996, Resuscitation.

[21]  J. Lindenfeld,et al.  Myocardial oxygen requirements during experimental cardiopulmonary resuscitation. , 1992, Cardiovascular research.

[22]  Petter Andreas Steen,et al.  The 1998 European Resuscitation Council guidelines for adult advanced life support , 1998, BMJ.

[23]  E. Gonzalez,et al.  Guidelines for cardiopulmonary resuscitation and emergency cardiac care. , 1987, Clinical pharmacy.

[24]  Wanchun Tang,et al.  Adverse effects of interrupting precordial compression during cardiopulmonary resuscitation. , 1997, Critical care medicine.