Confidence intervals and hypothesis testing for the Permutation Entropy with an application to epilepsy

Traversaro Varela, Francisco; Redelico, Francisco

artículo de publicación periódica.page.titleprefix
Confidence intervals and hypothesis testing for the Permutation Entropy with an application to epilepsy

dc.contributor.author	Traversaro Varela, Francisco
dc.contributor.author	Redelico, Francisco
dc.date.accessioned	2020-06-24T16:38:19Z
dc.date.available	2020-06-24T16:38:19Z
dc.date.issued	2018-04
dc.description.abstract	"In nonlinear dynamics, and to a lesser extent in other fields, a widely used measure of complexity is the Permutation Entropy. But there is still no known method to determine the accuracy of this measure. There has been little research on the statistical properties of this quantity that characterize time series. The literature describes some resampling methods of quantities used in nonlinear dynamics - as the largest Lyapunov exponent - but these seems to fail. In this contribution, we propose a parametric bootstrap methodology using a symbolic representation of the time series to obtain the distribution of the Permutation Entropy estimator. We perform several time series simulations given by well-known stochastic processes: the 1/f α noise family, and show in each case that the proposed accuracy measure is as efficient as the one obtained by the frequentist approach of repeating the experiment. The complexity of brain electrical activity, measured by the Permutation Entropy, has been extensively used in epilepsy research for detection in dynamical changes in electroencephalogram (EEG) signal with no consideration of the variability of this complexity measure. An application of the parametric bootstrap methodology is used to compare normal and pre-ictal EEG signals."	en
dc.identifier.issn	1007-5704
dc.identifier.uri	http://ri.itba.edu.ar/handle/123456789/2218
dc.language.iso	en	en
dc.relation	info:eu-repo/semantics/altIdentifier/doi/10.1016/j.cnsns.2017.10.013
dc.subject	EPILEPSIA	es
dc.subject	ENTROPIA	es
dc.subject	ELECTROENCEFALOGRAFIA	es
dc.subject	ANALISIS DE SERIES DE TIEMPO	es
dc.subject	PROCESAMIENTO DE SEÑALES DIGITALES	es
dc.title	Confidence intervals and hypothesis testing for the Permutation Entropy with an application to epilepsy	en
dc.type	Artículos de Publicaciones Periódicas	es
dc.type	info:eu-repo/semantics/acceptedVersion
dspace.entity.type	Artículo de Publicación Periódica
itba.description.filiation	Fil: Traversaro Varela, Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
itba.description.filiation	Fil: Traversaro Varela, Francisco. Instituto Tecnológico de Buenos Aires; Argentina.
itba.description.filiation	Fil: Redelico, Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
itba.description.filiation	Fil: Redelico, Francisco. Universidad Nacional de Quilmes; Argentina.
itba.description.filiation	Fil: Traversaro Varela, Francisco. Universidad Nacional de Lanús; Argentina.
itba.description.filiation	Fil: Redelico, Francisco. Hospital Italiano de Buenos Aires; Argentina.