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Comparative study of approximate entropy and sample entropy robustness to spikes

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Comparative study of approximate entropy and sample entropy robustness to spikes

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Molina Picó, A.; Cuesta Frau, D.; Riobo Aboy, PM.; Crespo Sánchez, MC.; Miró Martínez, P.; Oltra Crespo, S. (2011). Comparative study of approximate entropy and sample entropy robustness to spikes. Artificial Intelligence in Medicine. 53(2):97-106. doi:10.1016/j.artmed.2011.06.007

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/53709

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Title: Comparative study of approximate entropy and sample entropy robustness to spikes
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Universitat Politècnica de València. Instituto Agroforestal Mediterráneo - Institut Agroforestal Mediterrani
Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat
Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada
Issued date:
Abstract:
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 ...[+]
Subjects: Approximate entropy characterization , RR interval record classification , Sample entropy characterization , Signal spikes , Approximate entropy , Biomedical signal , Biomedical signal analysis , Comparative studies , Line spectra , Misclassifications , Narrow bands , QRS detection , Research efforts , RR intervals , Sample entropy , Synthetic signals , Test signal , Bioelectric phenomena , Random processes , Entropy , Article , Controlled study , Density , Electrocardiogram , Mathematical computing , Power spectral density , Priority journal , QRS complex , Sensitivity analysis , Spike wave , Stochastic model , Algorithms , Electrocardiography , Humans , Signal Processing, Computer-Assisted , Stochastic Processes
Copyrigths: Cerrado
Source:
Artificial Intelligence in Medicine. (issn: 0933-3657 )
DOI: 10.1016/j.artmed.2011.06.007
Publisher:
Elsevier
Publisher version: http://dx.doi.org/10.1016/j.artmed.2011.06.007
Thanks:
This work has been supported by the Spanish Ministry of Science and Innovation, research projects TEC2008-05871 and TEC2009-14222.
Type: Artículo

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