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Multi-Dimensional Enhanced Seizure Prediction Framework Based on Graph Convolutional Network
In terms of seizure prediction, how to fully mine relational data information among multiple channels of epileptic EEG? This is a scientific research subject worthy of further exploration. Recently, we propose a multi-dimensional enhanced seizure prediction framework, which mainly includes informati...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8417243/ https://www.ncbi.nlm.nih.gov/pubmed/34489667 http://dx.doi.org/10.3389/fninf.2021.605729 |
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author | Chen, Xin Zheng, Yuanjie Dong, Changxu Song, Sutao |
author_facet | Chen, Xin Zheng, Yuanjie Dong, Changxu Song, Sutao |
author_sort | Chen, Xin |
collection | PubMed |
description | In terms of seizure prediction, how to fully mine relational data information among multiple channels of epileptic EEG? This is a scientific research subject worthy of further exploration. Recently, we propose a multi-dimensional enhanced seizure prediction framework, which mainly includes information reconstruction space, graph state encoder, and space-time predictor. It takes multi-channel spatial relationship as breakthrough point. At the same time, it reconstructs data unit from frequency band level, updates graph coding representation, and explores space-time relationship. Through experiments on CHB-MIT dataset, sensitivity of the model reaches 98.61%, which proves effectiveness of the proposed model. |
format | Online Article Text |
id | pubmed-8417243 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84172432021-09-05 Multi-Dimensional Enhanced Seizure Prediction Framework Based on Graph Convolutional Network Chen, Xin Zheng, Yuanjie Dong, Changxu Song, Sutao Front Neuroinform Neuroscience In terms of seizure prediction, how to fully mine relational data information among multiple channels of epileptic EEG? This is a scientific research subject worthy of further exploration. Recently, we propose a multi-dimensional enhanced seizure prediction framework, which mainly includes information reconstruction space, graph state encoder, and space-time predictor. It takes multi-channel spatial relationship as breakthrough point. At the same time, it reconstructs data unit from frequency band level, updates graph coding representation, and explores space-time relationship. Through experiments on CHB-MIT dataset, sensitivity of the model reaches 98.61%, which proves effectiveness of the proposed model. Frontiers Media S.A. 2021-08-19 /pmc/articles/PMC8417243/ /pubmed/34489667 http://dx.doi.org/10.3389/fninf.2021.605729 Text en Copyright © 2021 Chen, Zheng, Dong and Song. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Chen, Xin Zheng, Yuanjie Dong, Changxu Song, Sutao Multi-Dimensional Enhanced Seizure Prediction Framework Based on Graph Convolutional Network |
title | Multi-Dimensional Enhanced Seizure Prediction Framework Based on Graph Convolutional Network |
title_full | Multi-Dimensional Enhanced Seizure Prediction Framework Based on Graph Convolutional Network |
title_fullStr | Multi-Dimensional Enhanced Seizure Prediction Framework Based on Graph Convolutional Network |
title_full_unstemmed | Multi-Dimensional Enhanced Seizure Prediction Framework Based on Graph Convolutional Network |
title_short | Multi-Dimensional Enhanced Seizure Prediction Framework Based on Graph Convolutional Network |
title_sort | multi-dimensional enhanced seizure prediction framework based on graph convolutional network |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8417243/ https://www.ncbi.nlm.nih.gov/pubmed/34489667 http://dx.doi.org/10.3389/fninf.2021.605729 |
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