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A Brief Survey of Computational Models of Normal and Epileptic EEG Signals: A Guideline to Model-based Seizure Prediction
In recent decades, seizure prediction has caused a lot of research in both signal processing and the neuroscience field. The researches have tried to enhance the conventional seizure prediction algorithms such that the rate of the false alarms be appropriately small, so that seizures can be predicte...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3317768/ https://www.ncbi.nlm.nih.gov/pubmed/22606660 |
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author | Shayegh, Farzaneh Fattahi, Rasoul Amir Sadri, Saeid Ansari-Asl, Karim |
author_facet | Shayegh, Farzaneh Fattahi, Rasoul Amir Sadri, Saeid Ansari-Asl, Karim |
author_sort | Shayegh, Farzaneh |
collection | PubMed |
description | In recent decades, seizure prediction has caused a lot of research in both signal processing and the neuroscience field. The researches have tried to enhance the conventional seizure prediction algorithms such that the rate of the false alarms be appropriately small, so that seizures can be predicted according to clinical standards. To date, none of the proposed algorithms have been sufficiently adequate. In this article we show that in considering the mechanism of the generation of seizures, the prediction results may be improved. For this purpose, an algorithm based on the identification of the parameters of a physiological model of seizures is introduced. Some models of electroencephalographic (EEG) signals that can also be potentially considered as models of seizure and some developed seizure models are reviewed. As an example the model of depth-EEG signals, proposed by Wendling, is studied and is shown to be a suitable model. |
format | Online Article Text |
id | pubmed-3317768 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-33177682012-05-09 A Brief Survey of Computational Models of Normal and Epileptic EEG Signals: A Guideline to Model-based Seizure Prediction Shayegh, Farzaneh Fattahi, Rasoul Amir Sadri, Saeid Ansari-Asl, Karim J Med Signals Sens Review Article In recent decades, seizure prediction has caused a lot of research in both signal processing and the neuroscience field. The researches have tried to enhance the conventional seizure prediction algorithms such that the rate of the false alarms be appropriately small, so that seizures can be predicted according to clinical standards. To date, none of the proposed algorithms have been sufficiently adequate. In this article we show that in considering the mechanism of the generation of seizures, the prediction results may be improved. For this purpose, an algorithm based on the identification of the parameters of a physiological model of seizures is introduced. Some models of electroencephalographic (EEG) signals that can also be potentially considered as models of seizure and some developed seizure models are reviewed. As an example the model of depth-EEG signals, proposed by Wendling, is studied and is shown to be a suitable model. Medknow Publications & Media Pvt Ltd 2011 /pmc/articles/PMC3317768/ /pubmed/22606660 Text en Copyright: © Journal of Medical Signals and Sensors http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Shayegh, Farzaneh Fattahi, Rasoul Amir Sadri, Saeid Ansari-Asl, Karim A Brief Survey of Computational Models of Normal and Epileptic EEG Signals: A Guideline to Model-based Seizure Prediction |
title | A Brief Survey of Computational Models of Normal and Epileptic EEG Signals: A Guideline to Model-based Seizure Prediction |
title_full | A Brief Survey of Computational Models of Normal and Epileptic EEG Signals: A Guideline to Model-based Seizure Prediction |
title_fullStr | A Brief Survey of Computational Models of Normal and Epileptic EEG Signals: A Guideline to Model-based Seizure Prediction |
title_full_unstemmed | A Brief Survey of Computational Models of Normal and Epileptic EEG Signals: A Guideline to Model-based Seizure Prediction |
title_short | A Brief Survey of Computational Models of Normal and Epileptic EEG Signals: A Guideline to Model-based Seizure Prediction |
title_sort | brief survey of computational models of normal and epileptic eeg signals: a guideline to model-based seizure prediction |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3317768/ https://www.ncbi.nlm.nih.gov/pubmed/22606660 |
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