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Listar por palabra clave "Electrocardiogram"

Mostrando ítems 1-20 de 51

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A novel wavelet-based filtering strategy to remove powerline interference from electrocardiograms with atrial fibrillation

García, M.; Martínez, Miguel; Ródenas, Juan; Rieta, J J; Alcaraz, R. (IOP Publishing, 2018)

[EN] Objective: The electrocardiogram (ECG) is currently the most widely used recording to diagnose cardiac disorders, including the most common supraventricular arrhythmia, such as atrial fibrillation (AF). However, ...
Alteration of the P-wave non-linear dynamics near the onset of paroxysmal atrial fibrillation

Martinez, Arturo; Abasolo, Daniel; Alcaraz, Raul; Rieta, J J (Elsevier, 2015-07)

The analysis of P-wave variability from the electrocardiogram (ECG) has been suggested as an early predictor of the onset of paroxysmal atrial fibrillation (PAP). Hence, a preventive treatment could be used to avoid the ...
Analisis de datos procedentes de estudios de neuro fisiologia en entornos de realidad virtual

Caballero Blas, Rodrigo (Universitat Politècnica de València, 2020-05-05)

[ES] El objetivo de la tesis fue investigar los métodos de eliminación de señales y artefactos previos al proceso en las señales de ECG y PPG. No solo, hemos evaluado e implementado algunos algoritmos existentes, sino que ...
Analysis of a deep learning algorithm to detect R peaks in ECG signals

Lafuente Alcázar, Beatriz (Universitat Politècnica de València, 2022-07-14)

[EN] Biomedical signals are a result of cells’ electrical activity, and the changes in their voltage. Electrocardiogram (ECG) signals are a specific type of biosignals, and they represent the main diagnostic tool for ...
Analysis of atrial fibrillation recidivity under successive attempts of electrical cardioversion based on fibrillatory wave amplitude and dominant frequency

Alcaraz Martínez, Raúl; Rieta, J J; Hornero, Fernando (2013)

Atrial fibrillation (AF) is the most common cardiac arrhythmia in clinical practice. One frequent and very effective alternative to revert AF back to a normal sinus rhythm (NSR) is external electrical cardioversion (ECV). ...
Application of artificial neural networks for versatile preprocessing of electrocardiogram recordings

Mateo, Jorge; Rieta Ibañez, José Joaquín (Informa Healthcare, 2012-02)

[EN] The electrocardiogram (ECG) is the most widely used method for diagnosis of heart diseases, where a good quality of recordings allows the proper interpretation and identification of physiological and pathological ...
Application of the relative wavelet energy to heart rate independent detection of atrial fibrillation

García, Manuel; Ródenas García, Juan; Alcaraz, Raúl; Rieta, J J (Elsevier, 2016-07)

Background and Objectives: Atrial fibrillation (AF) is the most common sustained cardiac ar- rhythmia and a growing healthcare burden worldwide. It is often asymptomatic and may appear as episodes of very short duration; ...
Assessment of non-invasive time and frequency atrial fibrillation organization markers with unipolar atrial electrograms

Alcaraz, Raúl; Hornero, Fernando; Rieta, J J (IOP Publishing: Hybrid Open Access, 2011-01)

The standard electrocardiogram (ECG) is the most common non-invasive way to study atrial fibrillation (AF). In this respect, previous works have shown that the surface lead V 1 reflects mainly the dominant atrial frequency ...
Biomedical signal analysis in automatic classification problems

Fuster García, Elíes (Editorial Universitat Politècnica de València, 2012-09-20)

A lo largo de la última década hemos asistido a un desarrollo sin precedentes de las tecnologías de la salud. Los avances en la informatización, la creación de redes, las técnicas de imagen, la robótica, las micro/nano ...
Central tendency measure and wavelet transform combined in the non-invasive analysis of atrial fibrillation recordings

Alcaraz, Raúl; Rieta Ibañez, José Joaquín (BioMed Central, 2012-08-09)

Background Atrial fibrillation (AF) is the most common supraventricular arrhythmia in the clinical practice, being the subject of intensive research. Methods The present work introduces two different Wavelet Transform ...
Classification of paroxysmal and persistent atrial fibrillation in ambulatory ECG recordings

Alcaraz, Raúl; Sandberg, Frida; Sornmo, Leif; Rieta Ibañez, José Joaquín (Institute of Electrical and Electronics Engineers (IEEE), 2011-05)

The problem of classifying short atrial fibrillatory segments in ambulatory ECG recordings as being either paroxysmal or persistent is addressed by investigating a robust approach to signal characterization. The method ...
Combination of frequency- and time-domain characteristics of the fibrillatory waves for enhanced prediction of persistent atrial fibrillation recurrence after catheter ablation

Escribano, Pilar; Ródenas, Juan; García, Manuel; Arias, Miguel A.; Hidalgo, Víctor M.; Calero, Sofía; Rieta, J J; Alcaraz, Raúl (Elsevier, 2024-02-15)

[EN] Catheter ablation (CA) remains the cornerstone alternative to cardioversion for sinus rhythm (SR) restoration in patients with atrial fibrillation (AF). Unfortunately, despite the last methodological and technological ...
Comparative assessment of nonlinear metrics to quantify organization-related events in surface electrocardiograms of atrial fibrillation

Julián, M.; Alcaraz, R.; Rieta, J J (Elsevier, 2014-05-01)

Atrial fibrillation (AF) is today the most common sustained arrhythmia, its treatment being not completely satisfactory. Electrical activity organization analysis within the atria could play a key role in the improvement ...
Comparative study of approximate entropy and sample entropy robustness to spikes

Molina Picó, Antonio; Cuesta Frau, David; Riobo Aboy, Pedro Mateo; Crespo Sánchez, María Cristina; Miró Martínez, Pau; Oltra Crespo, Sandra (Elsevier, 2011-10)

Objective: There is an ongoing research effort devoted to characterize the signal regularity metrics approximate entropy (ApEn) and sample entropy (SampEn) in order to better interpret their results in the context of ...
Comparison of Pre-Trained Deep Learning Algorithms for Quality Assessment of Electrocardiographic Recordings

Huerta, Álvaro; Martínez-Rodrigo, Arturo; Puchol, Alberto; Pachón, Marta I.; Alcaraz, Raúl; Rieta, J J (IEEE, 2020-10-30)

[EN] Convolutional neural networks (CNNs) have recently become popular for electrocardiogram (ECG) analysis. However, their ability for ECG quality assessment has still not been thoroughly assessed. This challenging topic, ...
Comparison of three artificial models of the magnetohydrodynamic effect on the electrocardiogram

Oster, Julien; Llinares Llopis, Raúl; Payne, Stephen; Tse, Zion Tsz Ho; Schmidt, Ehud Jeruham; Clifford, Gari D. (Taylor & Francis: STM, Behavioural Science and Public Health Titles, 2014-04-24)

The electrocardiogram (ECG) is often acquired during magnetic resonance imaging (MRI), but its analysis is restricted by the presence of a strong artefact, called magnetohydrodynamic (MHD) effect. MHD effect is induced by ...
Cuantificación de la organización intracardíaca de arritmias auriculares mediante la fase temporoespacial del electrocardiograma

Luz Carrillo, Daniel (Universitat Politècnica de València, 2016-05-11)

El objetivo principal del presente proyecto final de carrera persigue el desarrollo e implementación de métodos numéricos capaces de cuantificar la organización intracardíaca en registros electrocardiográficos procedentes ...
Desarrollo de modelos personalizados in silico para su utilización en población pediátrica

Pérez Herrero, Sandra (Universitat Politècnica de València, 2024-11-19)

[ES] A pesar de los recientes avances en los campos de la medicina y la tecnología, las enfermedades cardiovasculares continúan siendo la principal causa de mortalidad y morbilidad a nivel mundial. Estas enfermedades no ...
Design of a leads reconstruction algorithm for ambulatory ECG

Grande Fidalgo, Alejandro (Universitat Politècnica de València, 2019-09-06)

[ES] Las enfermedades cardiovasculares (ECV) causan 17,9 millones de muertes al año, el 31% del total de muertes en el mundo. La American Heart Association sostiene que la mayoría de los casos se pueden prevenir mediante ...
Development of an Artificial Intelligence model for COVID-19 detection based on electrocardiogram features

Moltó Miró, Juan (Universitat Politècnica de València, 2023-09-18)

[ES] Los objetivos de este proyecto son dos. En primer lugar, identificar características morfológicas clave en las señales de electrocardiograma (ECG) de 12 derivaciones que puedan ayudar a identificar a los pacientes ...