Epilepsy seizure onset detection applying 1-NN classifier based on statistical parameters

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"Epilepsy is a disease caused by an excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an ongoing challenge in biomedical signal processing. In this paper, a new method is proposed for onset seizure detection in epileptic EEG sign...

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Autores principales: Zorgno, Ivanna, Blanc, María Cecilia, Oxenford, Simón, Gil Garbagnoli, Francisco, D'Giano, Carlos, Quintero-Rincón, Antonio
Formato: Ponencias en Congresos acceptedVersion
Lenguaje:Inglés
Publicado: 2020
Materias:
ELECTROENCEFALOGRAFIA
PROCESAMIENTO DE SEÑALES DIGITALES
EPILEPSIA
Acceso en línea:http://ri.itba.edu.ar/handle/123456789/1855
Aporte de:
Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA) de Instituto Tecnológico de Buenos Aires (ITBA)
id I32-R138-123456789-1855
record_format dspace
spelling I32-R138-123456789-18552022-12-07T14:14:00Z Epilepsy seizure onset detection applying 1-NN classifier based on statistical parameters Zorgno, Ivanna Blanc, María Cecilia Oxenford, Simón Gil Garbagnoli, Francisco D'Giano, Carlos Quintero-Rincón, Antonio ELECTROENCEFALOGRAFIA PROCESAMIENTO DE SEÑALES DIGITALES EPILEPSIA "Epilepsy is a disease caused by an excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an ongoing challenge in biomedical signal processing. In this paper, a new method is proposed for onset seizure detection in epileptic EEG signals based on parameters from the t-location-scale distribution coupled with the variance and the Pearson correlation coefficient. The 1-nearest neighbor classifier achieved a 91% sensitivity (True positive rate) and 95% specificity (True Negative Rate) with a delay of 4.5 seconds (on average) in the 45 signals analyzed, which suggests that the proposed methodology is potentially useful for seizure onset detection in epileptic EEG signals." 2020-01-06T18:17:18Z 2020-01-06T18:17:18Z 2018 Ponencias en Congresos info:eu-repo/semantics/acceptedVersion http://ri.itba.edu.ar/handle/123456789/1855 en info:eu-repo/grantAgreement/ITBA/INICIACIÓN/2017/AR. Ciudad Autónoma de Buenos Aires info:eu-repo/semantics/altIdentifier/10.1109/ARGENCON.2018.8646234 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 ELECTROENCEFALOGRAFIA
PROCESAMIENTO DE SEÑALES DIGITALES
EPILEPSIA
spellingShingle ELECTROENCEFALOGRAFIA
PROCESAMIENTO DE SEÑALES DIGITALES
EPILEPSIA
Zorgno, Ivanna
Blanc, María Cecilia
Oxenford, Simón
Gil Garbagnoli, Francisco
D'Giano, Carlos
Quintero-Rincón, Antonio
Epilepsy seizure onset detection applying 1-NN classifier based on statistical parameters
topic_facet ELECTROENCEFALOGRAFIA
PROCESAMIENTO DE SEÑALES DIGITALES
EPILEPSIA
description "Epilepsy is a disease caused by an excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an ongoing challenge in biomedical signal processing. In this paper, a new method is proposed for onset seizure detection in epileptic EEG signals based on parameters from the t-location-scale distribution coupled with the variance and the Pearson correlation coefficient. The 1-nearest neighbor classifier achieved a 91% sensitivity (True positive rate) and 95% specificity (True Negative Rate) with a delay of 4.5 seconds (on average) in the 45 signals analyzed, which suggests that the proposed methodology is potentially useful for seizure onset detection in epileptic EEG signals."
format Ponencias en Congresos
acceptedVersion
author Zorgno, Ivanna
Blanc, María Cecilia
Oxenford, Simón
Gil Garbagnoli, Francisco
D'Giano, Carlos
Quintero-Rincón, Antonio
author_facet Zorgno, Ivanna
Blanc, María Cecilia
Oxenford, Simón
Gil Garbagnoli, Francisco
D'Giano, Carlos
Quintero-Rincón, Antonio
author_sort Zorgno, Ivanna
title Epilepsy seizure onset detection applying 1-NN classifier based on statistical parameters
title_short Epilepsy seizure onset detection applying 1-NN classifier based on statistical parameters
title_full Epilepsy seizure onset detection applying 1-NN classifier based on statistical parameters
title_fullStr Epilepsy seizure onset detection applying 1-NN classifier based on statistical parameters
title_full_unstemmed Epilepsy seizure onset detection applying 1-NN classifier based on statistical parameters
title_sort epilepsy seizure onset detection applying 1-nn classifier based on statistical parameters
publishDate 2020
url http://ri.itba.edu.ar/handle/123456789/1855
work_keys_str_mv AT zorgnoivanna epilepsyseizureonsetdetectionapplying1nnclassifierbasedonstatisticalparameters
AT blancmariacecilia epilepsyseizureonsetdetectionapplying1nnclassifierbasedonstatisticalparameters
AT oxenfordsimon epilepsyseizureonsetdetectionapplying1nnclassifierbasedonstatisticalparameters
AT gilgarbagnolifrancisco epilepsyseizureonsetdetectionapplying1nnclassifierbasedonstatisticalparameters
AT dgianocarlos epilepsyseizureonsetdetectionapplying1nnclassifierbasedonstatisticalparameters
AT quinterorinconantonio epilepsyseizureonsetdetectionapplying1nnclassifierbasedonstatisticalparameters
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