Universal fluctuations in very short ECG episodes
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Universal fluctuations in very short ECG episodes. / Bakucz, Peter; Willems, Stephan; Hoffmann, Boris A.
in: ACTA POLYTECH HUNG, Jahrgang 11, Nr. 7, 2014, S. 73-82.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
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TY - JOUR
T1 - Universal fluctuations in very short ECG episodes
AU - Bakucz, Peter
AU - Willems, Stephan
AU - Hoffmann, Boris A.
N1 - Publisher Copyright: © 2014, Budapest Tech Polytechnical Institution, All rights reserved.
PY - 2014
Y1 - 2014
N2 - We propose a new algorithm for the detection of ventricular fibrillation (VF) in very short surface electrocardiogram (ECG) episodes. Ventricular fibrillation is the most commonly identified arrhythmia in cardiac arrest patients and can lead to syncope, within seconds. The fast detection of ventricular fibrillation is necessary for prompt defibrillation either with an implantable cardioverter/defibrillator or an automated external defibrillator. Ventricular fibrillation generates stochastic waveforms and recently it has been shown that it exhibits characteristics similar to a non-chaotic signal and contains determinism Probability Density Function (PDF), for the different physical fluctuations was described previously. Accordingly, we describe scaling properties of very short shockable, VF and non-shockable ECG episodes and show that a universal PDF exists for the fluctuations of shockable ECG episodes. We compared the proposed algorithm with nine standard VF detection algorithms. The comparison indicated that our algorithm consistently produced more accurate detection results, then with standard algorithm. We conclude that the proposed method, based on fluctuation analysis, provides new information on the dynamics underlying VF, and allows a better detection compared to other algorithms.
AB - We propose a new algorithm for the detection of ventricular fibrillation (VF) in very short surface electrocardiogram (ECG) episodes. Ventricular fibrillation is the most commonly identified arrhythmia in cardiac arrest patients and can lead to syncope, within seconds. The fast detection of ventricular fibrillation is necessary for prompt defibrillation either with an implantable cardioverter/defibrillator or an automated external defibrillator. Ventricular fibrillation generates stochastic waveforms and recently it has been shown that it exhibits characteristics similar to a non-chaotic signal and contains determinism Probability Density Function (PDF), for the different physical fluctuations was described previously. Accordingly, we describe scaling properties of very short shockable, VF and non-shockable ECG episodes and show that a universal PDF exists for the fluctuations of shockable ECG episodes. We compared the proposed algorithm with nine standard VF detection algorithms. The comparison indicated that our algorithm consistently produced more accurate detection results, then with standard algorithm. We conclude that the proposed method, based on fluctuation analysis, provides new information on the dynamics underlying VF, and allows a better detection compared to other algorithms.
KW - Defibrillation
KW - Electrocardiogram
KW - Probability density function
KW - Universal fluctuations
KW - Ventricular fibrillation
UR - http://www.scopus.com/inward/record.url?scp=84907253282&partnerID=8YFLogxK
M3 - SCORING: Journal article
AN - SCOPUS:84907253282
VL - 11
SP - 73
EP - 82
JO - ACTA POLYTECH HUNG
JF - ACTA POLYTECH HUNG
SN - 1785-8860
IS - 7
ER -