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Cross-Subject Seizure Detection in EEGs Using Deep Transfer Learning
المؤلفون المشاركون
Hu, Dayi
Chen, Sirui
Zhang, Baocan
Xiao, Shixiao
Xiao, Yutian
Wang, Wennan
Chen, Shuaichen
Xu, Gaowei
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-05-08
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Electroencephalography (EEG) plays an import role in monitoring the brain activities of patients with epilepsy and has been extensively used to diagnose epilepsy.
Clinically reading tens or even hundreds of hours of EEG recordings is very time consuming.
Therefore, automatic detection of seizure is of great importance.
But the huge diversity of EEG signals belonging to different patients makes the task of seizure detection much challenging, for both human experts and automation methods.
We propose three deep transfer convolutional neural networks (CNN) for automatic cross-subject seizure detection, based on VGG16, VGG19, and ResNet50, respectively.
The original dataset is the CHB-MIT scalp EEG dataset.
We use short time Fourier transform to generate time-frequency spectrum images as the input dataset, while positive samples are augmented due to the infrequent nature of seizure.
The model parameters pretrained on ImageNet are transferred to our models.
And the fine-tuned top layers, with an output layer of two neurons for binary classification (seizure or nonseizure), are trained from scratch.
Then, the input dataset are randomly shuffled and divided into three partitions for training, validating, and testing the deep transfer CNNs, respectively.
The average accuracies achieved by the deep transfer CNNs based on VGG16, VGG19, and ResNet50 are 97.75%, 98.26%, and 96.17% correspondingly.
On those results of experiments, our method could prove to be an effective method for cross-subject seizure detection.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhang, Baocan& Wang, Wennan& Xiao, Yutian& Xiao, Shixiao& Chen, Shuaichen& Chen, Sirui…[et al.]. 2020. Cross-Subject Seizure Detection in EEGs Using Deep Transfer Learning. Computational and Mathematical Methods in Medicine،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1139585
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhang, Baocan…[et al.]. Cross-Subject Seizure Detection in EEGs Using Deep Transfer Learning. Computational and Mathematical Methods in Medicine No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1139585
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhang, Baocan& Wang, Wennan& Xiao, Yutian& Xiao, Shixiao& Chen, Shuaichen& Chen, Sirui…[et al.]. Cross-Subject Seizure Detection in EEGs Using Deep Transfer Learning. Computational and Mathematical Methods in Medicine. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1139585
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1139585
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
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