A deep learning scheme for automatic seizure detection from long-term scalp EEG
Epilepsy is a chronic brain disorder that is expressed by seizures. Monitoring brain activity
via electroencephalogram (EEG) is an established method for epilepsy diagnosis and for …
via electroencephalogram (EEG) is an established method for epilepsy diagnosis and for …
A novel epileptic seizure detection system using scalp EEG signals based on hybrid CNN-SVM classifier
Epilepsy is a neurological disorder that affects more than 2% of the world's population.
Encephalography (EEG) is a commonly clinical tool used for the diagnosis of epilepsy …
Encephalography (EEG) is a commonly clinical tool used for the diagnosis of epilepsy …
Epileptic seizure detection using deep convolutional autoencoder
AM Abdelhameed, HG Daoud… - 2018 IEEE international …, 2018 - ieeexplore.ieee.org
Monitoring and recording brain activities using Electroencephalograms (EEGs) has become
the foremost wide applied tool by physicians for epilepsy diagnosis due to viable reasons …
the foremost wide applied tool by physicians for epilepsy diagnosis due to viable reasons …
Epileptic seizure detection using deep convolutional network
L Zou, X Liu, A Jiang, X Zhousp - 2018 IEEE 23rd International …, 2018 - ieeexplore.ieee.org
In this paper, a patient specific seizure detection system using channel-restricted
convolutional neural network (CR-CNN) with deep structure is represented. The binary …
convolutional neural network (CR-CNN) with deep structure is represented. The binary …
Seizure and non-seizure EEG signals detection using 1-D convolutional neural network architecture of deep learning algorithm
TT Chowdhury, A Hossain, SA Fattah… - 2019 1st international …, 2019 - ieeexplore.ieee.org
In this paper, seizure activities of EEG signals have been detected exploiting 1-D
convolutional neural network architecture of deep learning algorithm. In past some years …
convolutional neural network architecture of deep learning algorithm. In past some years …
A Machine Learning Framework for Robust Epileptic Seizure Detection from EEG Sign
Millions of individuals throughout the world suffer from epilepsy, a neurological illness
characterized by frequent seizures. To improve patient safety and quality of life, seizure …
characterized by frequent seizures. To improve patient safety and quality of life, seizure …
[HTML][HTML] Automatic seizure detection based on imaged-EEG signals through fully convolutional networks
Seizure detection is a routine process in epilepsy units requiring manual intervention of well-
trained specialists. This process could be extensive, inefficient and time-consuming …
trained specialists. This process could be extensive, inefficient and time-consuming …
Automatic seizure detection using fully convolutional nested LSTM
The automatic seizure detection system can effectively help doctors to monitor and diagnose
epilepsy thus reducing their workload. Many outstanding studies have given good results in …
epilepsy thus reducing their workload. Many outstanding studies have given good results in …
[HTML][HTML] One dimensional convolutional neural networks for seizure onset detection using long-term scalp and intracranial EEG
Epileptic seizure detection using scalp electroencephalogram (sEEG) and intracranial
electroencephalogram (iEEG) has attracted widespread attention in recent two decades …
electroencephalogram (iEEG) has attracted widespread attention in recent two decades …
A new approach for classification of epilepsy eeg signals based on temporal convolutional neural networks
J Zhang, H Wu, W Su, X Wang… - 2018 11th international …, 2018 - ieeexplore.ieee.org
Epilepsy, a chronic disease, whose symptoms are sudden onset of brain neurons by the
abnormal discharge, leads to transient cerebral dysfunction. In recent years, the observation …
abnormal discharge, leads to transient cerebral dysfunction. In recent years, the observation …