Comparison of Frequency Bands Using Spectral Entropy for Epileptic Seizure Prediction

Under the hypothesis that the uncontrolled neuronal synchronization propagates recruitingmore andmore neurons, the aim is to detect its onset as early as possible by signal analysis.This synchronization is not noticeable just by looking at the EEG, somathematical tools are needed for its identific...

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Autores principales: Blanco, Susana, Garay, Arturo, Coulombie, Diego
Formato: Artículo
Lenguaje:Inglés
Publicado: Universidad de Belgrano - Facultad de Ingeniería y Tecnología Informática - Proyectos de Investigación 2015
Materias:
Frequency Bands
Spectral Entropy
Epileptic Seizure Prediction
Predicción ataque epiléptico
entropía espectral
Bandas de Frecuencia
Acceso en línea:http://repositorio.ub.edu.ar/handle/123456789/4857
Aporte de:
Repositorio Institucional - Universidad de Belgrano (UB) de Universidad de Belgrano
id I36-R142-123456789-4857
record_format dspace
institution Universidad de Belgrano
institution_str I-36
repository_str R-142
collection Repositorio Institucional - Universidad de Belgrano (UB)
language Inglés
topic Frequency Bands
Spectral Entropy
Epileptic Seizure Prediction
Predicción ataque epiléptico
entropía espectral
Bandas de Frecuencia
spellingShingle Frequency Bands
Spectral Entropy
Epileptic Seizure Prediction
Predicción ataque epiléptico
entropía espectral
Bandas de Frecuencia
Blanco, Susana
Garay, Arturo
Coulombie, Diego
Comparison of Frequency Bands Using Spectral Entropy for Epileptic Seizure Prediction
topic_facet Frequency Bands
Spectral Entropy
Epileptic Seizure Prediction
Predicción ataque epiléptico
entropía espectral
Bandas de Frecuencia
description Under the hypothesis that the uncontrolled neuronal synchronization propagates recruitingmore andmore neurons, the aim is to detect its onset as early as possible by signal analysis.This synchronization is not noticeable just by looking at the EEG, somathematical tools are needed for its identification.Objective.The aimof this study is to compare the results of spectral entropies calculated in different frequency bands of the EEG signals to decide which bandmay be a better tool to predict an epileptic seizure. Materials andMethods. Invasive ictal recordswere used.Wemeasured the Fourier spectrumentropy of the electroencephalographic signals 4 to 32minutes before the attack in low, mediumand high frequencies.Results.The high-frequency band shows amarkedly rate of increase of the entropy, with positive slopes and low correlation coefficient.The entropy rate of growth in the low-frequency band is practically zero, with a correlation around 0.2 and mostly positive slopes. The mid-frequency band showed both positive andnegativeslopeswithlowcorrelation.Conclusions. The entropy in the high frequencies could be predictor, because it shows changes in the previous moments of the attack. Its main problem is the variability, whichmakes it difficult to set the threshold that ensures an adequate prediction.
format Article
author Blanco, Susana
Garay, Arturo
Coulombie, Diego
author_facet Blanco, Susana
Garay, Arturo
Coulombie, Diego
author_sort Blanco, Susana
title Comparison of Frequency Bands Using Spectral Entropy for Epileptic Seizure Prediction
title_short Comparison of Frequency Bands Using Spectral Entropy for Epileptic Seizure Prediction
title_full Comparison of Frequency Bands Using Spectral Entropy for Epileptic Seizure Prediction
title_fullStr Comparison of Frequency Bands Using Spectral Entropy for Epileptic Seizure Prediction
title_full_unstemmed Comparison of Frequency Bands Using Spectral Entropy for Epileptic Seizure Prediction
title_sort comparison of frequency bands using spectral entropy for epileptic seizure prediction
publisher Universidad de Belgrano - Facultad de Ingeniería y Tecnología Informática - Proyectos de Investigación
publishDate 2015
url http://repositorio.ub.edu.ar/handle/123456789/4857
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AT garayarturo comparisonoffrequencybandsusingspectralentropyforepilepticseizureprediction
AT coulombiediego comparisonoffrequencybandsusingspectralentropyforepilepticseizureprediction
bdutipo_str Repositorios
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