[HTML][HTML] 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 …

Applying deep learning for epilepsy seizure detection and brain mapping visualization

MS Hossain, SU Amin, M Alsulaiman… - ACM Transactions on …, 2019 - dl.acm.org
Deep Convolutional Neural Network (CNN) has achieved remarkable results in computer
vision tasks for end-to-end learning. We evaluate here the power of a deep CNN to learn …

Scalp EEG classification using deep Bi-LSTM network for seizure detection

X Hu, S Yuan, F Xu, Y Leng, K Yuan, Q Yuan - Computers in Biology and …, 2020 - Elsevier
Automatic seizure detection technology not only reduces workloads of neurologists for
epilepsy diagnosis but also is of great significance for treatments of epileptic patients. 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 …

An EEG based real-time epilepsy seizure detection approach using discrete wavelet transform and machine learning methods

M Shen, P Wen, B Song, Y Li - Biomedical Signal Processing and Control, 2022 - Elsevier
Epilepsy is one of the most common complex brain disorders which is a chronic non-
communicable disease caused by paroxysmal abnormal super-synchronous electrical …

Automatic seizure detection using orthogonal matching pursuit, discrete wavelet transform, and entropy based features of EEG signals

A Zarei, BM Asl - Computers in Biology and Medicine, 2021 - Elsevier
Background and objective Epilepsy is a prevalent disorder that affects the central nervous
system, causing seizures. In the current study, a novel algorithm is developed using …

[HTML][HTML] Machine learning-based epileptic seizure detection methods using wavelet and EMD-based decomposition techniques: A review

RG Thangarajoo, MBI Reaz, G Srivastava, F Haque… - Sensors, 2021 - mdpi.com
Epileptic seizures are temporary episodes of convulsions, where approximately 70 percent
of the diagnosed population can successfully manage their condition with proper medication …

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 …

Alcoholic EEG signals recognition based on phase space dynamic and geometrical features

MT Sadiq, H Akbari, S Siuly, Y Li, P Wen - Chaos, Solitons & Fractals, 2022 - Elsevier
Alcoholism is a severe disorder that leads to brain problems and associated cognitive,
emotional and behavioral impairments. This disorder is typically diagnosed by a …