Automatic epileptic seizure detection based on empirical mode decomposition and deep neural network

HG Daoud, AM Abdelhameed… - 2018 IEEE 14th …, 2018 - ieeexplore.ieee.org
Electroencephalogram (EEG) used to record the electrical activity of the brain is a standout
amongst the most helpful tools which are utilized in the diagnosis of neurological disorders …

Detection of epileptic seizures by the analysis of EEG signals using empirical mode decomposition

S Yol, MA Ozdemir, A Akan… - 2018 Medical …, 2018 - ieeexplore.ieee.org
The detection of epileptic seizure has a primary role in patient diagnosis with epilepsy.
Epilepsy causes sudden and uncontrolled electrical discharges in brain cells. Recordings of …

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 …

Seizure type detection in epileptic EEG signal using empirical mode decomposition and support vector machine

I Wijayanto, R Hartanto, HA Nugroho… - … Seminar on Intelligent …, 2019 - ieeexplore.ieee.org
Epilepsy is a serious neurological disorder that needs more attention by society. The
International League Against Epilepsy (ILAE) mentioned that the term epilepsy referred to …

A deep learning-based method for automatic detection of epileptic seizure in a dataset with both generalized and focal seizure types

A Einizade, M Mozafari, SH Sardouie… - 2020 IEEE Signal …, 2020 - ieeexplore.ieee.org
Epilepsy is the second most popular neurological disorder affecting 65 million people
around the world. Seizures are classified into two kinds; focal and generalized ictal activities …

Empirical mode decomposition for deep learning-based epileptic seizure detection in few-shot scenario

Y Pan, F Dong, W Yao, X Meng, Y Xu - IEEE Access, 2024 - ieeexplore.ieee.org
The precise and automated detection of epileptic seizures has become a focal point of
research due to its potential to alleviate the severe consequences experienced by patients …

Epileptic seizure detection using multi-channel EEG wavelet power spectra and 1-D convolutional neural networks

RV Sharan, S Berkovsky - … of the IEEE Engineering in Medicine …, 2020 - ieeexplore.ieee.org
The use of feature extraction and selection from EEG signals has shown to be useful in the
detection of epileptic seizure segments. However, these traditional methods have more …

Semi-supervised EEG signals classification system for epileptic seizure detection

AM Abdelhameed, M Bayoumi - IEEE Signal Processing Letters, 2019 - ieeexplore.ieee.org
In the past few decades, measuring and recording the brain electrical activities using
Electroencephalogram (EEG) has become a standout amongst the tools utilized for …

Detection of pre-stage of epileptic seizure by exploiting temporal correlation of EMD decomposed EEG signals

M Parvez, M Paul, M Antolovich - Journal of Medical and …, 2015 - researchoutput.csu.edu.au
Epilepsy is one of the common neurological disorders characterized by a sudden and
recurrent malfunction of the brain that is termed “seizure”, affecting over 50 million …

Epileptic seizure detection from EEG signals using multiband features with feedforward neural network

KM Hassan, MR Islam, T Tanaka… - … on cyberworlds (CW), 2019 - ieeexplore.ieee.org
Electroencephalography (EEG) is considered as a potential tool for diagnosis of epilepsy in
clinical applications. Epileptic seizures occur irregularly and unpredictably. Its automatic …