Deep learning approach to detect seizure using reconstructed phase space images
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TLDR
The result of the proposed approach shows the prospect of employing RPS images with CNN for predicting epileptic seizures, and the performance of the convolution neural network (CNN) model is better than the other existing statistical approach for all performance indicators such as accuracy, sensitivity, and specificity.About:
This article is published in Journal of Biomedical Research.The article was published on 2020-05-28 and is currently open access. It has received 44 citations till now. The article focuses on the topics: Ictal & Image processing.read more
Citations
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Automatic identification of epileptic electroencephalography signals using higher-order spectra
TL;DR: The use of non-linear features motivated by the higher-order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal), and epileptic EEG signals.
Journal ArticleDOI
Detection of epileptic seizures on EEG signals using ANFIS classifier, autoencoders and fuzzy entropies
TL;DR: In this article , a novel diagnostic procedure using fuzzy theory and deep learning techniques is introduced, which is evaluated on the Bonn University dataset with six classification combinations and also on the Freiburg dataset.
Posted Content
Detection of Epileptic Seizures on EEG Signals Using ANFIS Classifier, Autoencoders and Fuzzy Entropies.
Afshin Shoeibi,Afshin Shoeibi,Navid Ghassemi,Marjane Khodatars,Parisa Moridian,Roohallah Alizadehsani,Assef Zare,Abbas Khosravi,Abdulhamit Subasi,U. Rajendra Acharya,Juan Manuel Górriz +10 more
TL;DR: In this paper, a novel diagnostic procedure using fuzzy theory and deep learning techniques is introduced, which is evaluated on the Bonn University dataset with six classification combinations and also on the Freiburg dataset.
Journal ArticleDOI
A Recent Investigation on Detection and Classification of Epileptic Seizure Techniques Using EEG Signal.
Sani Saminu,Guizhi Xu,Zhang Shuai,Isselmou Abd El Kader,Adamu Halilu Jabire,Yusuf Kola Ahmed,Ibrahim Abdullahi Karaye,Isah Salim Ahmad +7 more
TL;DR: In this paper, the benefits of early detection and classification of epileptic seizures in analysis, monitoring and diagnosis for the realization and actualization of computer-aided devices and recent internet of medical things (IoMT) devices can never be overemphasized.
Journal ArticleDOI
Automated Epileptic Seizure Detection in Pediatric Subjects of CHB-MIT EEG Database-A Survey.
J Prasanna,M. S. P. Subathra,Mazin Abed Mohammed,Robertas Damasevicius,Nanjappan Jothiraj Sairamya,S. Thomas George +5 more
TL;DR: In this article, the authors focused on various patient-dependent and patient-independent personalized medicine approaches involved in the computer-aided diagnosis of epileptic seizures in pediatric subjects by analyzing EEG signals.
References
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Proceedings Article
ImageNet Classification with Deep Convolutional Neural Networks
TL;DR: The state-of-the-art performance of CNNs was achieved by Deep Convolutional Neural Networks (DCNNs) as discussed by the authors, which consists of five convolutional layers, some of which are followed by max-pooling layers, and three fully-connected layers with a final 1000-way softmax.
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Efficient Processing of Deep Neural Networks: A Tutorial and Survey
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