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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...
The development of non-invasive tools able to provide valuable information about the effectiveness of a shock in external electrical cardioversion (ECV) is clinically relevant to enhance these protocols in the treatment of atrial fibrillation (AF). The present contribution analyzes the ability of a non-linear regularity index, such as sample entropy (SampEn), to follow-up noninvasively AF organization...
The analysis of the surface electrocardiogram (ECG) is the most extended noninvasive technique in medical diagnosis of atrial fibrillation (AF). In order to use the ECG as a tool for the analysis of AF, we need to separate the atrial activity (AA) from other cardioelectric signals. In this matter, statistical signal processing techniques, like independent component analysis (ICA) algorithms, are able...
The present work introduces a new ECG delineator, based on the Phasor Transform, which is able to operate in single lead recordings. The method converts each instantaneous ECG sample into a phasor, thus being able to deal very precisely with P and T waves, which are of notably lower amplitude than the QRS complex. Initially, the method relies on the detection of R peaks and, next, onset and offset...
Predicting non-invasively the effectiveness of a shock in external electrical cardioversion (ECV) is clinically relevant to enhance these protocols in the treatment of atrial fibrillation (AF). The present contribution analyzes the ability of a non-linear regularity index, such as sample entropy (SampEn), to follow-up noninvasively AF organization under successive attempts of ECV and to predict the...
Wavelet Sample Entropy (WSE) has been previously introduced as a successful methodology to predict electrical cardioversion (ECV) outcome of persistent atrial fibrillation (AF). The method estimates AF organization based on the combination of Wavelet decomposition and a nonlinear regularity metric, such as Sample Entropy (SampEn). However, WSE has been only computed by applying a specific wavelet...
In this work, a method for non-invasive assessment of AF organization has been applied to discriminating between paroxysmal and long-term persistent AF episodes. Following extraction of the atrial activity (AA) signal, the dominant atrial frequency (DAF) of the AA was computed based on a hidden Markov model. Finally, the main atrial wave (MAW) was obtained by bandpass filtering centered on the DAF,...
In the present work, three methods based on the Sample Entropy (SampEn) non-invasive organization estimation of atrial fibrillation (AF) to predict its spontaneous termination are compared making use of the same patient's database. In the first strategy, the atrial activity (AA) is obtained through QRST cancellation. Next, the main atrial wave (MAW) of the AA is obtained by selective filtering centered...
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