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Signal Analysis in Atrial Fibrillation

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Cardiovascular Computing—Methodologies and Clinical Applications

Part of the book series: Series in BioEngineering ((SERBIOENG))

Abstract

Recent advances and clinical applications of signal analysis in the characterization of the most common supra-ventricular arrhythmia, i.e. atrial fibrillation (AF), are summarized in this chapter. The analysis of invasive and non-invasive electrocardiographic signals has revealed useful clinical information in a broad variety of scenarios, thus opening new perspectives in the understanding of the currently unknown mechanisms triggering and maintaining the arrhythmia.

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Acknowledgements

This work has been supported by grants DPI2017–83952–C3 MINECO/AEI/FEDER, UE and SBPLY/17/180501/000411 from Junta de Comunidades de Castilla-La Mancha.

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Authors and Affiliations

  1. Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, Cuenca, Spain

    Raúl Alcaraz

  2. BioMIT.org, Electronic Engineering Department, Universidad Politécnica de Valencia, Valencia, Spain

    José J. Rieta

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  1. Raúl Alcaraz
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  2. José J. Rieta
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Correspondence to Raúl Alcaraz .

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Editors and Affiliations

  1. Medical School, National Kapodistrian University of Athens, Athens, Greece

    Spyretta Golemati

  2. Biomedical Simulations and Imaging Laboratory, National Technical University of Athens, Athens, Greece

    Konstantina S. Nikita

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Alcaraz, R., Rieta, J.J. (2019). Signal Analysis in Atrial Fibrillation. In: Golemati, S., Nikita, K. (eds) Cardiovascular Computing—Methodologies and Clinical Applications. Series in BioEngineering. Springer, Singapore. https://doi.org/10.1007/978-981-10-5092-3_17

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