Sparse spectral analysis of atrial fibrillation electrograms

Monzón García, Sandra and Trigano, Tom and Luengo García, David and Artés Rodríguez, Antonio (2012). Sparse spectral analysis of atrial fibrillation electrograms. In: "2012 IEEE International Workshop on Machine Learning for Signal Processing, Sept. 23–26, 2012, Santander, Spain", 23/09/2012 - 26/02/2014, Santander. ISBN 978-1-4673-1026-0. pp. 1-6. https://doi.org/10.1109/MLSP.2012.6349721.

Description

Title: Sparse spectral analysis of atrial fibrillation electrograms
Author/s:
  • Monzón García, Sandra
  • Trigano, Tom
  • Luengo García, David
  • Artés Rodríguez, Antonio
Item Type: Presentation at Congress or Conference (Article)
Event Title: 2012 IEEE International Workshop on Machine Learning for Signal Processing, Sept. 23–26, 2012, Santander, Spain
Event Dates: 23/09/2012 - 26/02/2014
Event Location: Santander
Title of Book: Proceedings of the 2012 IEEE International Workshop on Machine Learning and Signal Processing (MLSP)
Date: 2012
ISBN: 978-1-4673-1026-0
Subjects:
Freetext Keywords: sparsity-aware learning, spectral analysis, atrial fibrillation, biomedical signal processing
Faculty: E.U.I.T. Telecomunicación (UPM)
Department: Ingeniería de Circuitos y Sistemas [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Atrial fibrillation (AF) is a common heart disorder. One of the most prominent hypothesis about its initiation and maintenance considers multiple uncoordinated activation foci inside the atrium. However, the implicit assumption behind all the signal processing techniques used for AF, such as dominant frequency and organization analysis, is the existence of a single regular component in the observed signals. In this paper we take into account the existence of multiple foci, performing a spectral analysis to detect their number and frequencies. In order to obtain a cleaner signal on which the spectral analysis can be performed, we introduce sparsity-aware learning techniques to infer the spike trains corresponding to the activations. The good performance of the proposed algorithm is demonstrated both on synthetic and real data. RESUMEN. Algoritmo basado en técnicas de regresión dispersa para la extracción de las señales cardiacas en pacientes con fibrilación atrial (AF).

More information

Item ID: 22893
DC Identifier: http://oa.upm.es/22893/
OAI Identifier: oai:oa.upm.es:22893
DOI: 10.1109/MLSP.2012.6349721
Official URL: http://mlsp2012.conwiz.dk/
Deposited by: Memoria Investigacion
Deposited on: 26 Mar 2014 20:37
Last Modified: 21 Apr 2016 20:49
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