EEG seizure detection and prediction algorithms: a survey

TN Alotaiby, SA Alshebeili, T Alshawi, I Ahmad… - EURASIP Journal on …, 2014 - Springer
Epilepsy patients experience challenges in daily life due to precautions they have to take in
order to cope with this condition. When a seizure occurs, it might cause injuries or endanger …

Automated epileptic seizure detection in pediatric subjects of CHB-MIT EEG database—a survey

J Prasanna, MSP Subathra, MA Mohammed… - Journal of Personalized …, 2021 - mdpi.com
Epilepsy is a neurological disorder of the brain that causes frequent occurrence of seizures.
Electroencephalography (EEG) is a tool that assists neurologists in detecting epileptic …

An automated system for epilepsy detection using EEG brain signals based on deep learning approach

I Ullah, M Hussain, H Aboalsamh - Expert Systems with Applications, 2018 - Elsevier
Epilepsy is a life-threatening and challenging neurological disorder, which is affecting a
large number of people all over the world. For its detection, encephalography (EEG) is a …

Epileptic seizure detection in EEG signals using a unified temporal-spectral squeeze-and-excitation network

Y Li, Y Liu, WG Cui, YZ Guo, H Huang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The intelligent recognition of epileptic electro-encephalogram (EEG) signals is a valuable
tool for the epileptic seizure detection. Recent deep learning models fail to fully consider …

A multivariate approach for patient-specific EEG seizure detection using empirical wavelet transform

A Bhattacharyya, RB Pachori - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Objective: This paper investigates the multivariate oscillatory nature of
electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure …

Optimized deep neural network architecture for robust detection of epileptic seizures using EEG signals

R Hussein, H Palangi, RK Ward, ZJ Wang - Clinical Neurophysiology, 2019 - Elsevier
Objective Automatic detection of epileptic seizures based on deep learning methods
received much attention last year. However, the potential of deep neural networks in seizure …

[HTML][HTML] One dimensional convolutional neural networks for seizure onset detection using long-term scalp and intracranial EEG

X Wang, X Wang, W Liu, Z Chang, T Kärkkäinen… - Neurocomputing, 2021 - Elsevier
Epileptic seizure detection using scalp electroencephalogram (sEEG) and intracranial
electroencephalogram (iEEG) has attracted widespread attention in recent two decades …

Deep multi-view feature learning for EEG-based epileptic seizure detection

X Tian, Z Deng, W Ying, KS Choi, D Wu… - … on Neural Systems …, 2019 - ieeexplore.ieee.org
Epilepsy is a neurological illness caused by abnormal discharge of brain neurons, where
epileptic seizure can lead to life-threatening emergencies. By analyzing the encephalogram …

EEG signal analysis for diagnosing neurological disorders using discrete wavelet transform and intelligent techniques

FA Alturki, K AlSharabi, AM Abdurraqeeb, M Aljalal - Sensors, 2020 - mdpi.com
Analysis of electroencephalogram (EEG) signals is essential because it is an efficient
method to diagnose neurological brain disorders. In this work, a single system is developed …

Epileptic seizure detection: A deep learning approach

R Hussein, H Palangi, R Ward, ZJ Wang - arxiv preprint arxiv:1803.09848, 2018 - arxiv.org
Epilepsy is the second most common brain disorder after migraine. Automatic detection of
epileptic seizures can considerably improve the patients' quality of life. Current …