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Nonlinear measures characterize atrial fibrillatory dynamics generated using fractional diffusion
dc.creator | Ugarte J.P. | spa |
dc.creator | Duque S.I. | spa |
dc.creator | Duque A.O. | spa |
dc.creator | Tobón C. | spa |
dc.creator | Bustamante J. | spa |
dc.creator | Andrade-Caicedo H. | spa |
dc.date.accessioned | 2017-12-19T19:36:42Z | |
dc.date.available | 2017-12-19T19:36:42Z | |
dc.date.created | 2017 | |
dc.identifier.isbn | 9789811040856 | |
dc.identifier.issn | 16800737 | |
dc.identifier.uri | http://hdl.handle.net/11407/4258 | |
dc.description.abstract | Computational simulations are used as tool to study atrial fibrillation and its maintaining mechanisms. Phase analysis has been used to elucidate the mechanisms by which a reentry is generated. However, clinical application of phase mapping requires a signal preprocessing stage that could affect the activation sequences. In this work we use the fractional diffusion equation to generate fibrillatory dynamics, including stable and meandering rotors, and multiple wavelets, by varying the order of the spatial fractional derivatives obtaining different complexity levels of propagation in a 2D domain. We applied nonlinear measures to characterize the propagation patterns from electrograms. Our results show that electroanatomical maps constructed using approximate entropy and multifractal analysis, are able to detect the tip of stable and meandering rotors, and to mark the occurrence of collisions and wave breaks. Application of these signal processing techniques to clinical practice is feasible and could improve atrial fibrillation ablation procedures. © Springer Nature Singapore Pte Ltd. 2017. | eng |
dc.language.iso | eng | |
dc.publisher | Springer Verlag | spa |
dc.relation.isversionof | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018383521&doi=10.1007%2f978-981-10-4086-3_136&partnerID=40&md5=6ca3f6c0bfc02238feb5e0952ffe2eff | spa |
dc.source | Scopus | spa |
dc.title | Nonlinear measures characterize atrial fibrillatory dynamics generated using fractional diffusion | spa |
dc.type | Conference Paper | eng |
dc.rights.accessrights | info:eu-repo/semantics/restrictedAccess | |
dc.contributor.affiliation | Ugarte, J.P., Grupo de Dinámica Cardiovascular, Universidad Pontificia Bolivariana, Medellín, Colombia | spa |
dc.contributor.affiliation | Duque, S.I., Grupo de Dinámica Cardiovascular, Universidad Pontificia Bolivariana, Medellín, Colombia | spa |
dc.contributor.affiliation | Duque, A.O., Grupo de Investigación e Innovación Biomédica, Instituto Tecnológico Metropolitano, Medellín, Colombia | spa |
dc.contributor.affiliation | Tobón, C., Grupo de Investigación en Materiales Nanoestructurados y Biomodelación, Universidad de Medellín, Medellín, Colombia | spa |
dc.contributor.affiliation | Bustamante, J., Grupo de Dinámica Cardiovascular, Universidad Pontificia Bolivariana, Medellín, Colombia | spa |
dc.contributor.affiliation | Andrade-Caicedo, H., Grupo de Dinámica Cardiovascular, Universidad Pontificia Bolivariana, Medellín, Colombia | spa |
dc.identifier.doi | 10.1007/978-981-10-4086-3_136 | |
dc.subject.keyword | Atrial fibrillation | eng |
dc.subject.keyword | Fractional diffusion | eng |
dc.subject.keyword | Nonlinear measures | eng |
dc.subject.keyword | Phase analysis | eng |
dc.subject.keyword | Rotors | eng |
dc.subject.keyword | Ablation | eng |
dc.subject.keyword | Biomedical engineering | eng |
dc.subject.keyword | Diffusion | eng |
dc.subject.keyword | Diseases | eng |
dc.subject.keyword | Rotors | eng |
dc.subject.keyword | Signal processing | eng |
dc.subject.keyword | Atrial fibrillation | eng |
dc.subject.keyword | Computational simulation | eng |
dc.subject.keyword | Fractional derivatives | eng |
dc.subject.keyword | Fractional diffusion | eng |
dc.subject.keyword | Fractional diffusion equation | eng |
dc.subject.keyword | Nonlinear measure | eng |
dc.subject.keyword | Phase analysis | eng |
dc.subject.keyword | Signal processing technique | eng |
dc.subject.keyword | Nonlinear analysis | eng |
dc.publisher.faculty | Facultad de Ciencias Básicas | spa |
dc.abstract | Computational simulations are used as tool to study atrial fibrillation and its maintaining mechanisms. Phase analysis has been used to elucidate the mechanisms by which a reentry is generated. However, clinical application of phase mapping requires a signal preprocessing stage that could affect the activation sequences. In this work we use the fractional diffusion equation to generate fibrillatory dynamics, including stable and meandering rotors, and multiple wavelets, by varying the order of the spatial fractional derivatives obtaining different complexity levels of propagation in a 2D domain. We applied nonlinear measures to characterize the propagation patterns from electrograms. Our results show that electroanatomical maps constructed using approximate entropy and multifractal analysis, are able to detect the tip of stable and meandering rotors, and to mark the occurrence of collisions and wave breaks. Application of these signal processing techniques to clinical practice is feasible and could improve atrial fibrillation ablation procedures. © Springer Nature Singapore Pte Ltd. 2017. | eng |
dc.creator.affiliation | Grupo de Dinámica Cardiovascular, Universidad Pontificia Bolivariana, Medellín, Colombia | spa |
dc.creator.affiliation | Grupo de Investigación e Innovación Biomédica, Instituto Tecnológico Metropolitano, Medellín, Colombia | spa |
dc.creator.affiliation | Grupo de Investigación en Materiales Nanoestructurados y Biomodelación, Universidad de Medellín, Medellín, Colombia | spa |
dc.relation.ispartofes | IFMBE Proceedings | spa |
dc.relation.ispartofes | IFMBE Proceedings Volume 60, 2017, Pages 541-544 | spa |
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dc.relation.references | January Craig, T., Samuel, W. L., & Alpert, J. S. (2014). AHA/ACC/HRS Guideline for the Management of Patients with Atrial Fibrillation: Executive Summary Journal of the American College of Cardiology. | spa |
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dc.relation.references | Liu, F., Turner, I., Anh, V., Yang, Q., & Burrage, K. (2012). A numerical method for the fractional fitzhugh,nagumo monodomain model. ANZIAM Journal, 54(SUPPL), C608-C629. | spa |
dc.relation.references | Mathias, B., Prashanthan, S., & Ganesan, A. (2016). Quantitative-Electrogram-Based Methods for Guiding Catheter Ablation in Atrial Fibrillation Proceeding of the IEEE, 104, 416-431. | spa |
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dc.relation.references | Narayan, S. M., Krummen, D. E., Shivkumar, K., Clopton, P., Rappel, W. -., & Miller, J. M. (2012). Treatment of atrial fibrillation by the ablation of localized sources: CONFIRM (conventional ablation for atrial fibrillation with or without focal impulse and rotor modulation) trial. Journal of the American College of Cardiology, 60(7), 628-636. doi:10.1016/j.jacc.2012.05.022 | spa |
dc.relation.references | Orozco-Duque, A., Novak, D., Kremen, V., & Bustamante, J. (2015). Multifractal analysis for grading complex fractionated electrograms in atrial fibrillation. Physiological Measurement, 36(11), 2269-2284. doi:10.1088/0967-3334/36/11/2269 | spa |
dc.relation.references | Pincus, S. M. (1991). Approximate entropy as a measure of system complexity. Proceedings of the National Academy of Sciences of the United States of America, 88(6), 2297-2301. | spa |
dc.relation.references | Ugarte, J. P., Orozco-Duque, A., & Tobón, C. (2014). Dynamic Approximate Entropy Electroanatomic Maps Detect Rotors in a Simulated Atrial Fibrillation Model Plos One, 9. | spa |
dc.type.version | info:eu-repo/semantics/publishedVersion | |
dc.type.driver | info:eu-repo/semantics/conferenceObject | |
dc.identifier.reponame | reponame:Repositorio Institucional Universidad de Medellín | spa |
dc.identifier.instname | instname:Universidad de Medellín | spa |
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