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Detection of Arrhythmic Cardiac Signals from ECG Recordings Using the Entropy–Complexity Plane

1
Signals and Images Processing Centre (CPSI), Facultad Regional Buenos Aires, Universidad Tecnológica Nacional, Medrano 951, Buenos Aires C1179AAQ, Argentina
2
Bioengineering Development and Research Laboratory (GIBIO), Facultad Regional Buenos Aires, Universidad Tecnológica Nacional, Medrano 951, Buenos Aires C1179AAQ, Argentina
*
Author to whom correspondence should be addressed.
Presented at the 5th International Electronic Conference on Entropy and Its Applications, 18–30 November 2019; Available online: https://ecea-5.sciforum.net/.
Proceedings 2020, 46(1), 8; https://doi.org/10.3390/ecea-5-06693
Published: 18 November 2019
The aim of this work was to analyze in the Entropy–Complexity plane (HxC) time series coming from ECG, with the objective to discriminate recordings from two different groups of patients: normal sinus rhythm and cardiac arrhythmias. The HxC plane used in this study was constituted by Shannon’s Entropy as one of its axes, and the other was composed using statistical complexity. To compute the entropy, the probability distribution function (PDF) of the observed data was obtained using the methodology proposed by Bandt and Pompe (2002). The database used in the present study was the ECG recordings obtained from PhysioNet, 47 long-term signals of patients with diagnosed cardiac arrhythmias and 18 long-term signals from normal sinus rhythm patients were processed. Average values of statistical complexity and normalized Shannon entropy were calculated and analyzed in the HxC plane for each time series. The average values of complexity of ECG for patients with diagnosed arrhythmias were bigger than normal sinus rhythm group. On the other hand, the Shannon entropy average values for arrhythmias patients were lower than the normal sinus rhythm group. This characteristic made it possible to discriminate the position of both signals’ groups in the HxC plane. The results were analyzed through a multivariate statistical test hypothesis. The methodology proposed has a remarkable conceptual simplicity, and shows a promising efficiency in the detection of cardiovascular pathologies.
Keywords: entropy–complexity plane; ECG; arrhythmic cardiac signals; Shannon’s entropy; permutation entropy; Bandt and Pompe entropy–complexity plane; ECG; arrhythmic cardiac signals; Shannon’s entropy; permutation entropy; Bandt and Pompe
MDPI and ACS Style

Coq, P.M.; Legnani, W.; Armentano, R. Detection of Arrhythmic Cardiac Signals from ECG Recordings Using the Entropy–Complexity Plane. Proceedings 2020, 46, 8. https://doi.org/10.3390/ecea-5-06693

AMA Style

Coq PM, Legnani W, Armentano R. Detection of Arrhythmic Cardiac Signals from ECG Recordings Using the Entropy–Complexity Plane. Proceedings. 2020; 46(1):8. https://doi.org/10.3390/ecea-5-06693

Chicago/Turabian Style

Coq, Pablo Martinez; Legnani, Walter; Armentano, Ricardo. 2020. "Detection of Arrhythmic Cardiac Signals from ECG Recordings Using the Entropy–Complexity Plane" Proceedings 46, no. 1: 8. https://doi.org/10.3390/ecea-5-06693

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