Francisco Castells

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In the past few decades, analysis of heart sound signals (i.e. the phonocardiogram or PCG), especially for automated heart sound segmentation and classification, has been widely studied and has been reported to have the potential value to detect pathology accurately in clinical applications. However, comparative analyses of algorithms in the literature have(More)
This contribution addresses the extraction of atrial activity (AA) from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). We show the appropriateness of independent component analysis (ICA) to tackle this biomedical challenge when regarded as a blind source separation (BSS) problem. ICA is a statistical tool able to reconstruct the(More)
The analysis and characterization of atrial tachyarrhythmias requires, in a previous step, the extraction of the atrial activity (AA) free from ventricular activity and other artefacts. This contribution adopts the blind source separation (BSS) approach to AA estimation from multilead electrocardiograms (ECGs). Previously proposed BSS methods for AA(More)
A new method for the assessment of the atrial fibrillatory wave (AFW) from the ECG is presented. This methodology is suitable for signals registered from Holter systems, where the reduced number of leads is insufficient to exploit the spatial information of the ECG. The temporal dependence of the bio-electrical activity were exploited using principal(More)
1Grupo de Investigación en Bioingeneŕıa, Electrónica y Telemedicina, Departamento de Ingeneŕıa Electrónica, Escuela Politécnica Superior de Gandı́a, Universidad Politécnica de Valencia (UPV), Ctra. Nazaret-Oliva, 46730 Gandı́a, Spain 2Communications Technology Group, Aragón Institute of Engineering Research, University of Zaragoza, 50018 Zaragoza, Spain 3(More)
Independent component analysis (ICA) is an emerging technique for multidimensional signal processing. In recent years, these techniques have been proposed for solving a large number of biomedical applications. This work reviews current knowledge on ICA in electrocardiographic (ECG) analysis. The benefits that ICA can bring to clinical practice are(More)
The analysis and characterization of atrial fibrillation requires the previous extraction of the atrial activity from the electrocardiogram, where the independent atrial and ventricular activities are combined in addition to noise. An independent component analysis method is proposed where additional knowledge about the time and statistical structure of the(More)
INTRODUCTION Invasive high-density mapping of atrial fibrillation (AF) has revealed different patterns of atrial activation ranging from single wavefronts to disorganized activation with multiple simultaneous wavefronts. Whether or not similar activation patterns can also be observed using body surface recordings is currently unknown, and was consequently(More)
A novel automated approach to quantitatively evaluate the degree of spatio-temporal organization in the atrial activity (AA) during atrial fibrillation (AF) from surface recordings, obtained from body surface potential maps (BSPM), is presented. AA organization is assessed by measuring the reflection of the spatial complexity and temporal stationarity of(More)