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Study of Sample Entropy ideal computational parameters in the estimation of atrial fibrillation organization from the ECG

Alcaraz, R, Abásolo, D, Hornero, R and Rieta, JJ (2010) Study of Sample Entropy ideal computational parameters in the estimation of atrial fibrillation organization from the ECG

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Sample Entropy (SampEn) is a nonlinear regularity index that requires the a priori selection of three parameters: the length of the sequences to be compared, m, the patterns similarity tolerance, r, and the number of samples under analysis, N. Appropriate values for m, r and N have been recommended in some cases, such as heart rate, hormonal data, etc., but no guidelines exist for the selection of that values. Hence, an optimal parameters study should be required for the application of SampEn to not previously analyzed biomedical signals. In this work, a thorough analysis on the optimal SampEn parameter values within two different scenarios of AF organization estimation, such as the prediction of paroxysmal AF termination and the electrical cardioversion outcome in persistent AF, is presented. Results indicated that, (i) the proportion between N and the sampling rate (f) should be higher than one second and f ≥ 256 Hz, (ii) overlapping between adjacent N-length windows does not improve organization estimation and (iii) values of m and r maximizing classification should be considered within a range wider than the proposed in the literature for heart rate analysis.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Authors :
Alcaraz, R
Abásolo, D
Hornero, R
Rieta, JJ
Date : 2010
Additional Information : CinC Papers On-line Since volume 33 (2006), CinC has been an open-access publication, in which copyright in each article is held by its authors, who grant permission to copy and redistribute their work with attribution, under the terms of the Creative Commons Attribution License.
Depositing User : Symplectic Elements
Date Deposited : 13 Nov 2012 20:28
Last Modified : 31 Oct 2017 14:41

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