Cristobal Sanchez

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Discrimination between normal sinus rhythm (NSR), Atrial Fibrillation (AF) and Atrial Flutter (AFL) using the surface electrocardiogram (ECG) through direct Fourier analysis is not effective because ventricular activity (VA) overlaps in frequency with atrial activity (AA) and, moreover, AA frequency components present considerably lower amplitude than VA.(More)
Detection of atrial activity (AA) is quite important in the study and monitoring of atrial rhythms, in particular atrial flutter and atrial fibrillation (FA). An efficient non-invasive study of the AA needs the ventricular activity cancellation. The Discrete Packet Wavelet Transform (DPWT) allows the decomposition of the original ECG in a set of(More)
In this work, the aim is to discriminate terminating from non terminating atrial fibrillation (AF) episodes. A database including a learning set with 20 recordings and a test set with 30 recordings was provided. We hypothesized that the most relevant information about the mechanisms that trigger the AF is contained in the atrial fibrillatory wave (FW),(More)
Atrial Fibrillation (AF) episodes are commonly encountered in the daily clinical practice and cardiologists have often to face the difficulty of classifying between terminating and non-terminating AF episodes. Given that in these critical situations a decision must be made with the utmost urgency, it would be desirable to have a visualization tool of easy(More)
In this contribution, we present the theoretical justification that give support to the suitability of Blind Signal Separation (BSS) techniques for the estimation of the atrial activity (AA) present in ECGs of persistent atrial fibrillation (AF). The application of BSS methods to this problem needs the fulfillment of several conditions regarding AA,(More)
The mechanisms that provoke the eventual termination of some self paroxysmal fibrillation (PAF) episodes still remain unexplained. The aim of this to discriminate between between the groups of terminating (T registers) and non-terminating (N registers) of PAF episodes by using the ECG. A new technique, called Wavelet Sample En-tropy (WSE) is proposed. WSE(More)
Given the high prevalence of Atrial Fibrillation (AF) among adult population, to distinguish between these AF episodes that terminate spontaneously and those that persist if no external action is carried out becomes a subject of great clinical interest. In this matter, the complexity analysis of mathematical sequences of parameters obtained from(More)
Abnormal adaptation of action potential duration (APD) to changes in heart rate (HR) has been suggested as an indicator of increased arrhythmic risk. In this study, we investigate the mechanisms underlying APD rate adaptation in human atrial cells and its relationship to arrhythmogenesis. Simulations are performed using action potential computational models(More)
In this contribution is presented a new method for estimating the atrial activity (AA) from one-lead atrial fibrillation (AF) ECGs. This methodology is appropriate for holter signals, where the reduced number of leads is insufficient to exploit the spatial information of the ECG. The proposed approach is based on principal component analysis (PCA) concepts,(More)
This study shows the possibility of atrial activity (AA) extraction from atrial fibrillation (AF) episodes in Holter registers using only two leads (V1 and V5) with a new technique, the Wavelet Blind Separation (WBS). The WBS increases the observed mixtures of the original signal from the decomposition of each lead into six transformed signals using a(More)