[HTML][HTML] Epileptic seizures detection using deep learning techniques: a review

A Shoeibi, M Khodatars, N Ghassemi, M Jafari… - International journal of …, 2021 - mdpi.com
A variety of screening approaches have been proposed to diagnose epileptic seizures,
using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities …

An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works

A Shoeibi, P Moridian, M Khodatars… - Computers in biology …, 2022 - Elsevier
Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure
include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand …

Detection of epileptic seizures on EEG signals using ANFIS classifier, autoencoders and fuzzy entropies

A Shoeibi, N Ghassemi, M Khodatars… - … Signal Processing and …, 2022 - Elsevier
Epileptic seizures are one of the most crucial neurological disorders, and their early
diagnosis will help the clinicians to provide accurate treatment for the patients. The …

A hybrid deep learning approach for epileptic seizure detection in EEG signals

I Ahmad, X Wang, D Javeed, P Kumar… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Early detection and proper treatment of epilepsy is essential and meaningful to those who
suffer from this disease. The adoption of deep learning (DL) techniques for automated …

Epileptic seizure detection based on bidirectional gated recurrent unit network

Y Zhang, S Yao, R Yang, X Liu, W Qiu… - … on Neural Systems …, 2022 - ieeexplore.ieee.org
Visual inspection of long-term electroencephalography (EEG) is a tedious task for
physicians in neurology. Based on bidirectional gated recurrent unit (Bi-GRU) neural …

Patient-independent seizure detection based on channel-perturbation convolutional neural network and bidirectional long short-term memory

G Liu, L Tian, W Zhou - International journal of neural systems, 2022 - World Scientific
Automatic seizure detection is of great significance for epilepsy diagnosis and alleviating the
massive burden caused by manual inspection of long-term EEG. At present, most seizure …

Automatic epileptic seizure detection in EEG signals using sparse common spatial pattern and adaptive short-time Fourier transform-based synchrosqueezing …

M Amiri, H Aghaeinia, HR Amindavar - Biomedical Signal Processing and …, 2023 - Elsevier
Epilepsy can now be diagnosed more accurately and quickly due to computer-aided seizure
detection utilizing Electroencephalography (EEG) recordings. In this work, a novel method …

Epileptic Seizure Prediction Using Attention Augmented Convolutional Network.

D Liu, X Dong, D Bian, W Zhou - International Journal of Neural …, 2023 - europepmc.org
Early seizure prediction is crucial for epilepsy patients to reduce accidental injuries and
improve their quality of life. Identifying pre-ictal EEG from the inter-ictal state is particularly …

Detection of epileptic seizures from EEG signals by combining dimensionality reduction algorithms with machine learning models

M Zubair, MV Belykh, MUK Naik… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
Epilepsy is a neurological condition that affects the central nervous system. While its effects
are different for each person, they mostly include abnormal behaviour, periods of loss of …

Significant low-dimensional spectral-temporal features for seizure detection

X Yan, D Yang, Z Lin, B Vucetic - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
Absence seizure as a generalized onset seizure, simultaneously spreading seizure to both
sides of the brain, involves around ten-second sudden lapses of consciousness. It common …