- -

Comparative study of approximate entropy and sample entropy robustness to spikes

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

Comparative study of approximate entropy and sample entropy robustness to spikes

Show simple item record

Files in this item

dc.contributor.author Molina Picó, Antonio es_ES
dc.contributor.author Cuesta Frau, David es_ES
dc.contributor.author Riobo Aboy, Pedro Mateo es_ES
dc.contributor.author Crespo Sánchez, María Cristina es_ES
dc.contributor.author Miró Martínez, Pau es_ES
dc.contributor.author Oltra Crespo, Sandra es_ES
dc.date.accessioned 2015-07-24T11:38:11Z
dc.date.available 2015-07-24T11:38:11Z
dc.date.issued 2011-10
dc.identifier.issn 0933-3657
dc.identifier.uri http://hdl.handle.net/10251/53709
dc.description.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 biomedical signal analysis. Along with this line, this paper addresses the influence of abnormal spikes (impulses) on ApEn and SampEn measurements. Methods: A set of test signals consisting of generic synthetic signals, simulated biomedical signals, and real RR records was created. These test signals were corrupted by randomly generated spikes. ApEn and SampEn were computed for all the signals under different spike probabilities and for 100 realizations. Results: The effect of the presence of spikes on ApEn and SampEn is different for test signals with narrowband line spectra and test signals that are better modeled as broadband random processes. In the first case, the presence of extrinsic spikes in the signal results in an ApEn and SampEn increase. In the second case, it results in an entropy decrease. For real RR records, the presence of spikes, often due to QRS detection errors, also results in an entropy decrease. Conclusions: Our findings demonstrate that both ApEn and SampEn are very sensitive to the presence of spikes. Abnormal spikes should be removed, if possible, from signals before computing ApEn or SampEn. Otherwise, the results can lead to misunderstandings or misclassification of the signal regularity. © 2011 Elsevier B.V. es_ES
dc.description.sponsorship This work has been supported by the Spanish Ministry of Science and Innovation, research projects TEC2008-05871 and TEC2009-14222. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation Spanish Ministry of Science and Innovation TEC2008-05871 TEC2009-14222 es_ES
dc.relation.ispartof Artificial Intelligence in Medicine es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Approximate entropy characterization es_ES
dc.subject RR interval record classification es_ES
dc.subject Sample entropy characterization es_ES
dc.subject Signal spikes es_ES
dc.subject Approximate entropy es_ES
dc.subject Biomedical signal es_ES
dc.subject Biomedical signal analysis es_ES
dc.subject Comparative studies es_ES
dc.subject Line spectra es_ES
dc.subject Misclassifications es_ES
dc.subject Narrow bands es_ES
dc.subject QRS detection es_ES
dc.subject Research efforts es_ES
dc.subject RR intervals es_ES
dc.subject Sample entropy es_ES
dc.subject Synthetic signals es_ES
dc.subject Test signal es_ES
dc.subject Bioelectric phenomena es_ES
dc.subject Random processes es_ES
dc.subject Entropy es_ES
dc.subject Article es_ES
dc.subject Controlled study es_ES
dc.subject Density es_ES
dc.subject Electrocardiogram es_ES
dc.subject Mathematical computing es_ES
dc.subject Power spectral density es_ES
dc.subject Priority journal es_ES
dc.subject QRS complex es_ES
dc.subject Sensitivity analysis es_ES
dc.subject Spike wave es_ES
dc.subject Stochastic model es_ES
dc.subject Algorithms es_ES
dc.subject Electrocardiography es_ES
dc.subject Humans es_ES
dc.subject Signal Processing, Computer-Assisted es_ES
dc.subject Stochastic Processes es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.title Comparative study of approximate entropy and sample entropy robustness to spikes es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.artmed.2011.06.007
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Agroforestal Mediterráneo - Institut Agroforestal Mediterrani es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada es_ES
dc.description.bibliographicCitation 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 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.artmed.2011.06.007 es_ES
dc.description.upvformatpinicio 97 es_ES
dc.description.upvformatpfin 106 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 53 es_ES
dc.description.issue 2 es_ES
dc.relation.senia 201560


This item appears in the following Collection(s)

Show simple item record