Epileptic-net: an improved epileptic seizure detection system using dense convolutional block with attention network from EEG

MS Islam, K Thapa, SH Yang - Sensors, 2022 - mdpi.com
Epilepsy is a complex neurological condition that affects a large number of people
worldwide. Electroencephalography (EEG) measures the electrical activity of the brain and …

A difference attention ResNet-LSTM network for epileptic seizure detection using EEG signal

X Qiu, F Yan, H Liu - Biomedical Signal Processing and Control, 2023 - Elsevier
Epileptic seizures can affect the patient's physical function and cause irreversible damage to
their brain. It is vital to detect epilepsy seizures in time and give patients antiepileptic …

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 …

SeizureNet: a model for robust detection of epileptic seizures based on convolutional neural network

W Zhao, W Wang - Cognitive Computation and Systems, 2020 - Wiley Online Library
Epilepsy is a neurological disorder and generally detected by electroencephalogram (EEG)
signals. The manual inspection of epileptic seizures is a time‐consuming and laborious …

Epilepsy-Net: attention-based 1D-inception network model for epilepsy detection using one-channel and multi-channel EEG signals

A Lebal, A Moussaoui, A Rezgui - Multimedia Tools and Applications, 2023 - Springer
In this paper, we propose and evaluate Epilepsy-Net, a collection of deep learning EEG
signal processing tools to detect epileptic seizures against non-epileptic seizures without …

CNN based framework for detection of epileptic seizures

M Sameer, B Gupta - Multimedia tools and applications, 2022 - Springer
Epilepsy is a common neurological disease that uses electroencephalogram (EEG) data for
its detection purpose. Neurologists make the diagnosis by visual inspection of EEG reports …

Lightweight Seizure Detection Based on Multi-Scale Channel Attention.

Z Wang, S Hou, T Xiao, Y Zhang, H Lv, J Li… - … Journal of Neural …, 2023 - europepmc.org
Epilepsy is one kind of neurological disease characterized by recurring seizures. Recurrent
seizures can cause ongoing negative mental and cognitive damage to the patient …

HyEpiSeiD: a hybrid convolutional neural network and gated recurrent unit model for epileptic seizure detection from electroencephalogram signals

R Bhadra, PK Singh, M Mahmud - Brain Informatics, 2024 - Springer
Epileptic seizure (ES) detection is an active research area, that aims at patient-specific ES
detection with high accuracy from electroencephalogram (EEG) signals. The early detection …

Effective Detection of Epileptic Seizures through EEG Signals Using Deep Learning Approaches

S Mekruksavanich, A Jitpattanakul - Machine Learning and Knowledge …, 2023 - mdpi.com
Epileptic seizures are a prevalent neurological condition that impacts a considerable portion
of the global population. Timely and precise identification can result in as many as 70% of …

Studying multi-frequency multilayer brain network via deep learning for EEG-based epilepsy detection

W Dang, D Lv, L Rui, Z Liu, G Chen… - IEEE sensors journal, 2021 - ieeexplore.ieee.org
Epilepsy makes the patients suffer great pain and has a very bad impact on daily life. In this
paper, a novel method is proposed to implement electroencephalogram (EEG)-based …