Deep convolutional bidirectional LSTM recurrent neural network for epileptic seizure detection

AM Abdelhameed, HG Daoud… - 2018 16th IEEE …, 2018 - ieeexplore.ieee.org
Recording the brain electrical activities using Electroencephalogram (EEG) has become the
most widely applied tool by physicians for the diagnosis of neurological disorders. In this …

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 …

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 …

A CNN-LSTM hybrid network for automatic seizure detection in EEG signals

S Shanmugam, S Dharmar - Neural Computing and Applications, 2023 - Springer
Epilepsy is a chronic neurological disorder. Epileptics are prone to sudden seizures that
cause disruptions in their daily lives. The separation of epileptic and non-epileptic activity on …

Automated epilepsy seizure detection from EEG signal based on hybrid CNN and LSTM model

SK Pandey, RR Janghel, PK Mishra… - Signal, Image and Video …, 2023 - Springer
Epilepsy is a neurological disorder that affects the normal functioning of the brain. More than
10% of the population across the globe is affected by this disorder. Electroencephalogram …

Epileptic seizure detection for multi-channel EEG with deep convolutional neural network

C Park, G Choi, J Kim, S Kim, TJ Kim… - 2018 International …, 2018 - ieeexplore.ieee.org
A new epileptic seizure detection method based on deep convolutional network is proposed.
The proposed network is designed for multi-channel EEG signals and considers spatio …

FPGA implementation of high accuracy automatic epileptic seizure detection system

HG Daoud, AM Abdelhameed… - 2018 IEEE 61st …, 2018 - ieeexplore.ieee.org
Analysis of Electroencephalogram (EEG) records acquired from the brain is considered the
easiest and a powerful tool in diagnosis the neurological disorders that are related to the …

A LSTM-CNN Model for Epileptic Seizures Detection using EEG Signal

N Jiwani, K Gupta, MHU Sharif… - … on Emerging Smart …, 2022 - ieeexplore.ieee.org
Neurologists visually inspect electroencephalogram (EEG) reports to get the epilepsy
diagnosis. Scholars have suggested automated techniques to detect the ailment due to the …

[HTML][HTML] Convolutional neural network-based fast seizure detection from video electroencephalograms

CH Chou, TW Shen, H Tung, PF Hsieh, CE Kuo… - … Signal Processing and …, 2023 - Elsevier
Objective Ictal stage detection in electroencephalography (EEG) is important for epilepsy
diagnosis. However, it'sa laborious and time-consuming task for neurologists, especially …

Deep classification of epileptic signals

D Ahmedt-Aristizabal, C Fookes… - 2018 40th Annual …, 2018 - ieeexplore.ieee.org
Electrophysiological observation plays a major role in epilepsy evaluation. However, human
interpretation of brain signals is subjective and prone to misdiagnosis. Automating this …