A Convolutional Gated Recurrent Neural Network for Epileptic Seizure Prediction

被引：21

作者：

Affes, Abir ^{[1
]}

Mdhaffar, Afef ^{[1
,2
]}

Triki, Chahnez ^{[3
]}

Jmaiel, Mohamed ^{[1
,2
]}

Freisleben, Bernd ^{[4
]}

机构：

[1] Univ Sfax, ReDCAD Lab, ENIS, BP 1173, Sfax, Tunisia

[2] Digital Res Ctr Sfax, Sfax 3021, Tunisia

[3] Hosp Hedi Chaker, Dept Child Neurol, Sfax 3029, Tunisia

[4] Philipps Univ Marburg, Dept Math & Comp Sci, Marburg, Germany

来源：

HOW AI IMPACTS URBAN LIVING AND PUBLIC HEALTH, ICOST 2019 | 2019年 / 11862卷

关键词：

Epilepsy; Elecroencephalogram; Spectrogram; STFT; CNN; GRU; Seizure prediction; INTERNATIONAL-LEAGUE; ILAE;

D O I：

10.1007/978-3-030-32785-9_8

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we present a convolutional gated recurrent neural network (CGRNN) to predict epileptic seizures based on features extracted from EEG data that represent the temporal aspect and the frequency aspect of the signal. Using a dataset collected in the Children's Hospital of Boston, CGRNN can predict epileptic seizures between 35 min and 5 min in advance. Our experimental results indicate that the performance of CGRNN varies between patients. We achieve an average sensitivity of 89% and a mean accuracy of 75.6% for the patients in the data set, with a mean False Positive Rate (FPR) of 1.6 per hour.

引用

页码：85 / 96

页数：12

共 50 条

[1] Epileptic Seizure Prediction with Recurrent Convolutional Neural Networks
Ozcan, Ahmet Remzi
Erturk, Sarp
[J]. 2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2017,
[2] Epileptic Seizure Prediction Based on Convolutional Recurrent Neural Network with Multi-Timescale
Duan, Lijuan
Hou, Jinze
Qiao, Yuanhua
Miao, Jun
[J]. INTELLIGENCE SCIENCE AND BIG DATA ENGINEERING: BIG DATA AND MACHINE LEARNING, PT II, 2019, 11936 : 139 - 150
[3] A Convolutional Gated Recurrent Neural Network for Seizure Onset Localization
Daoud, Hisham
Bayoumi, Magdy
[J]. 2020 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE, 2020, : 2572 - 2576
[4] Convolutional Neural Networks for Epileptic Seizure Prediction
Eberlein, Matthias
Hildebrand, Raphael
Tetzlaff, Ronald
Hoffmann, Nico
Kuhlmann, Levin
Brinkmann, Benjamin
Mueller, Jens
[J]. PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM), 2018, : 2577 - 2582
[5] Deep Convolutional Bidirectional LSTM Recurrent Neural Network for Epileptic Seizure Detection
Abdelhameed, Ahmed M.
Daoud, Hisham G.
Bayoumi, Magdy
[J]. 2018 16TH IEEE INTERNATIONAL NEW CIRCUITS AND SYSTEMS CONFERENCE (NEWCAS), 2018, : 139 - 143
[6] HyEpiSeiD: a hybrid convolutional neural network and gated recurrent unit model for epileptic seizure detection from electroencephalogram signals
Bhadra, Rajdeep
Singh, Pawan Kumar
Mahmud, Mufti
[J]. BRAIN INFORMATICS, 2024, 11 (01)
[7] Epileptic Seizure Prediction: A Multi-Scale Convolutional Neural Network Approach
Hussein, Ramy
Ward, Rabab
[J]. 2019 7TH IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (IEEE GLOBALSIP), 2019,
[8] Epileptic Seizure Prediction: A Semi-Dilated Convolutional Neural Network Architecture
Hussein, Ramy
Lee, Soojin
Ward, Rabab
McKeown, Martin J.
[J]. 2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2021, : 5436 - 5443
[9] Epileptic seizure prediction based on local mean decomposition and deep convolutional neural network
Yu, Zuyi
Nie, Weiwei
Zhou, Weidong
Xu, Fangzhou
Yuan, Shasha
Leng, Yan
Yuan, Qi
[J]. JOURNAL OF SUPERCOMPUTING, 2020, 76 (05): : 3462 - 3476
[10] Epileptic seizure prediction based on local mean decomposition and deep convolutional neural network
Zuyi Yu
Weiwei Nie
Weidong Zhou
Fangzhou Xu
Shasha Yuan
Yan Leng
Qi Yuan
[J]. The Journal of Supercomputing, 2020, 76 : 3462 - 3476

← 1 2 3 4 5 →