A new algorithm for automatic identification of spike-wave EEG signals in epileptic patient-specific

"Appropriate diagnosis and treatment of epilepsy is a main public health issue. Patients suffering from this disease often exhibit different physical characterizations, which results from the synchronous and excessive discharge of a group of neurons in the cerebral cortex. Extracting this infor...

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Autores principales: Racca, Dora María, Quintero-Rincón, Antonio, Muro, Valeria, D'Giano, Carlos
Formato: Póster
Lenguaje:Inglés
Publicado: 2019
Materias:
EPILEPSIA
ELECTROENCEFALOGRAFIA
PROCESAMIENTO DE SEÑALES DIGITALES
Acceso en línea:http://ri.itba.edu.ar/handle/123456789/1603
Aporte de:
Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA) de Instituto Tecnológico de Buenos Aires (ITBA)
id I32-R138-123456789-1603
record_format dspace
spelling I32-R138-123456789-16032022-12-07T15:14:47Z A new algorithm for automatic identification of spike-wave EEG signals in epileptic patient-specific Racca, Dora María Quintero-Rincón, Antonio Muro, Valeria D'Giano, Carlos EPILEPSIA ELECTROENCEFALOGRAFIA PROCESAMIENTO DE SEÑALES DIGITALES "Appropriate diagnosis and treatment of epilepsy is a main public health issue. Patients suffering from this disease often exhibit different physical characterizations, which results from the synchronous and excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an important problem in biomedical processing. In this work we propose a new method to indentify and characterize patient specific spike-and-wave EEG epileptic signals. The method is based on the use of trained neuronal networks on probability density function parameters of the translation and rescaling of the Student'st-distribution (location: µ,scale: σ and shape: ν) of pure spike-and-wave-signals. The neuronal network was trained with both normal and epileptic signals. The study resulted in 100% specificity and sensitivity on the studied signals." 2019-05-29T17:17:01Z 2019-05-29T17:17:01Z 2018 Póster http://ri.itba.edu.ar/handle/123456789/1603 en info:eu-repo/grantAgreement/ITBA/ITBACyT/2016/AR. Ciudad Autónoma de Buenos Aires info:eu-repo/grantAgreement/ITBA/ITBACyT/2017/AR. Ciudad Autónoma de Buenos Aires application/pdf
institution Instituto Tecnológico de Buenos Aires (ITBA)
institution_str I-32
repository_str R-138
collection Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA)
language Inglés
topic EPILEPSIA
ELECTROENCEFALOGRAFIA
PROCESAMIENTO DE SEÑALES DIGITALES
spellingShingle EPILEPSIA
ELECTROENCEFALOGRAFIA
PROCESAMIENTO DE SEÑALES DIGITALES
Racca, Dora María
Quintero-Rincón, Antonio
Muro, Valeria
D'Giano, Carlos
A new algorithm for automatic identification of spike-wave EEG signals in epileptic patient-specific
topic_facet EPILEPSIA
ELECTROENCEFALOGRAFIA
PROCESAMIENTO DE SEÑALES DIGITALES
description "Appropriate diagnosis and treatment of epilepsy is a main public health issue. Patients suffering from this disease often exhibit different physical characterizations, which results from the synchronous and excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an important problem in biomedical processing. In this work we propose a new method to indentify and characterize patient specific spike-and-wave EEG epileptic signals. The method is based on the use of trained neuronal networks on probability density function parameters of the translation and rescaling of the Student'st-distribution (location: µ,scale: σ and shape: ν) of pure spike-and-wave-signals. The neuronal network was trained with both normal and epileptic signals. The study resulted in 100% specificity and sensitivity on the studied signals."
format Póster
author Racca, Dora María
Quintero-Rincón, Antonio
Muro, Valeria
D'Giano, Carlos
author_facet Racca, Dora María
Quintero-Rincón, Antonio
Muro, Valeria
D'Giano, Carlos
author_sort Racca, Dora María
title A new algorithm for automatic identification of spike-wave EEG signals in epileptic patient-specific
title_short A new algorithm for automatic identification of spike-wave EEG signals in epileptic patient-specific
title_full A new algorithm for automatic identification of spike-wave EEG signals in epileptic patient-specific
title_fullStr A new algorithm for automatic identification of spike-wave EEG signals in epileptic patient-specific
title_full_unstemmed A new algorithm for automatic identification of spike-wave EEG signals in epileptic patient-specific
title_sort new algorithm for automatic identification of spike-wave eeg signals in epileptic patient-specific
publishDate 2019
url http://ri.itba.edu.ar/handle/123456789/1603
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