A New Algorithmic Method to Detect Ventricular Fibrillation Using Electrocardiogram Signals During Cardiopulmonary Resuscitation by Artificial Pressing_Journal of Biomedical Engineering

Authors：

Institute of medical equipment, Academy of military medical science, Tianjin 300161, China;

Corresponding author：

Keywords：

chest compressions; ventricular fibrillation rhythm; normal sinus rhythm; filtering; electrocardiographic rhythm diagnosis

DOI：

10.7507/1001-5515.20160122

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On account of the mechanical disturbance of external chest pressing to electrocardiogram (ECG) signal, the ECG rhythm cannot be identified reliably during the cardio-pulmonary resuscitation period. Whereas the possibility of successful resuscitation will be lowered due to interrupted external chest pressing, a new filtering algorithm, enhanced leastmean-square (eLMS) algorithm, was proposed and developed in our laboratory. The algorithm can filter the disturbance of external chest pressing without the support of hardware reference signal and correctly identify ventricular fibrillation (VF) rhythm and normal sinus rhythm in case of uninterrupted external chest pressing. Without other reference signals, this algorithm realizes filtering only through the interrupted electrocardiograma (cECG) signal. It was verified with ECG signal and disturbance signal under different signal to noise ratios and contrasted with other mature algorithms. The verification results showed that the identification effect of eLMS was superior to those of others under different signal to noise ratios. Furthermore, ECG rhythm can be correctly identified only through cECG signal. This algorithm not only reduces the research and development(R & D)costs of automated external defibrillator but also raises the identification accuracy of ECG rhythm and the possibility of successful resuscitation.

Citation： WANGDan, ZHANGGuang, WANZongming, CHENFeng, SONGZhenxing, WANGHaitao, GUBiao, YUMing, WUTaihu. A New Algorithmic Method to Detect Ventricular Fibrillation Using Electrocardiogram Signals During Cardiopulmonary Resuscitation by Artificial Pressing. Journal of Biomedical Engineering, 2016, 33(4): 747-754, 761. doi: 10.7507/1001-5515.20160122 Copy

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1. WAALEWIJN R A, DE VOS R, KOSTER R W. Out-of-hospital cardiac arrests in Amsterdam and its surrounding areas:results from the Amsterdam resuscitation study (ARREST) in 'Utstein' style[J]. Resuscitation, 1998, 38(3):157-167.
2. REA T D, EISENBERG M S, SINIBALDI G, et al. Incidence of EMS-treated out-of-hospital cardiac arrest in the United States[J]. Resuscitation, 2004, 63(1):17-24.
3. VALENZUELA T D, ROE D J, NICHOL G, et al. Outcomes of rapid defibrillation by security officers after cardiac arrest in casinos[J]. N Engl J Med, 2000, 343(17):1206-1209.
4. HANDLEY A J, KOSTER R, MONSIEURS K, et al. European resuscitation council guidelines for resuscitation 2005. section 2. adult basic Life support and use of automated external defibrillators[J]. Resuscitation, 2005, 67(Suppl 1):S7-S23.
5. SNYDER D, MORGAN C. Wide variation in cardiopulmonary resuscitation interruption intervals among commercially available automated external defibrillators May affect survival despite high defibrillation efficacy[J]. Crit Care Med, 2004, 32(9 Suppl):S421-S424.
6. CUMMINS R O, EISENBERG M, BERGNER L, et al. SENSITIVITY, ACCURACY, AND SAFETY OF AN AUTOMATIC EXTERNAL DEFIBRILLATOR-Report of a Field Evaluation[J]. Lancet, 1984, 2(8398):318-320.
7. VAN ALEM A P, SANOU B T, KOSTER R W. Interruption of cardiopulmonary resuscitation with the use of the automated external defibrillator in out-of-hospital cardiac arrest[J]. Ann Emerg Med, 2003, 42(4):449-457.
8. SATO Y, WEIL M H, SUN S, et al. Adverse effects of interrupting precordial compression during cardiopulmonary resuscitation[J]. Crit Care Med, 1997, 25(5):733-736.
9. EFTESTØL T, SUNDE K, STEEN P A. Effects of interrupting precordial compressions on the calculated probability of defibrillation success during out-of-hospital cardiac arrest[J]. Circulation, 2002, 105(19):2270-2273.
10. YU Ting, WEIL M H, TANG Wanchun, et al. Adverse outcomes of interrupted precordial compression during automated defibrillation[J]. Circulation, 2002, 106(3):368-372.
11. KERN K B, HILWIG R W, BERG R A, et al. Importance of continuous chest compressions during cardiopulmonary resuscitation:improved outcome during a simulated single lay-rescuer scenario[J]. Circulation, 2002, 105(5):645-649.
12. AASE S O, EFTESTØL T, HUSØY J H, et al. CPR artifact removal from human ECG using optimal multichannel filtering[J]. IEEE Trans Biomed Eng, 2000, 47(11):1440-1449.
13. HUSØY J H, EILEVSTJØNN J, EFTESTØL T, et al. Removal of cardiopulmonary resuscitation artifacts from human ECG using an efficient matching pursuit-like algorithm[J]. IEEE Trans Biomed Eng, 2002, 49(11):1287-1298.
14. LANGHELLE A, EFTESTØL T, MYKLEBUST H, et al. Reducing CPR artefacts in ventricular fibrillation in vitro[J]. Resuscitation, 2001, 48(3):279-291.
15. EILEVSTJØNN J, EFTESTØL T, AASE S O, et al. Feasibility of shock advice analysis during CPR through removal of CPR artefacts from the human ECG[J]. Resuscitation, 2004, 61(2):131-141.
16. IRUSTA U, RUIZ J, DE GAUNA S R, et al. A least mean-square filter for the estimation of the cardiopulmonary resuscitation artifact based on the frequency of the compressions[J]. IEEE Trans Biomed Eng, 2009, 56(4):1052-1062.
17. ARAMENDI E, DE GAUNA S R, IRUSTA U, et al. Detection of ventricular fibrillation in the presence of cardiopulmonary resuscitation artefacts[J]. Resuscitation, 2007, 72(1):115-123.
18. RUIZ DE GAUNA S, RUIZ J, IRUSTA U, et al. A method to remove CPR artefacts from human ECG using only the recorded ECG[J]. Resuscitation, 2008, 76(2):271-278.
19. LI Yongqin, BISERA J, WEIL M H, et al. An algorithm used for ventricular fibrillation detection without interrupting chest compression[J]. IEEE Trans Biomed Eng, 2012, 59(1):78-86.
20. AMANN A, TRATNIG R, UNTERKOFLER K. Detecting ventricular fibrillation by time-delay methods[J]. IEEE Trans Biomed Eng, 2007, 54(1):174-177.
21. Research Resources for Complex Physiologic Signals National Center for Research Resources of the National Institutes of Health. Creighton UniversityVentricular Tachyarrhythmia Database[DB/OL]. (2000)[2015-04-07]. http://www.physionet.org/physiobank/database/cudb.
22. Research Resources for Complex Physiologic Signals National Center for Research Resources of the National Institutes of Health. Malignant Ventricular Arrhythmia Database[DB/OL]. (2000)[2015-04-08]. http://physionet.org/physiobank/database/vfdb/.
23. RHEINBERGER K, STEINBERGER T, UNTERKOFLER K, et al. Removal of CPR artifacts from the ventricular fibrillation ECG by adaptive regression on lagged reference signals[J]. IEEE Trans Biomed Eng, 2008, 55(1):130-137.
24. WERTHER T, KLOTZ A, KRACHER G, et al. CPR artifact removal in ventricular fibrillation ECG signals using Gabor multipliers[J]. IEEE Trans Biomed Eng, 2009, 56(2):320-327.

Journal of Biomedical Engineering

A New Algorithmic Method to Detect Ventricular Fibrillation Using Electrocardiogram Signals During Cardiopulmonary Resuscitation by Artificial Pressing

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