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 …

Review of machine and deep learning techniques in epileptic seizure detection using physiological signals and sentiment analysis

DP Dash, M Kolekar, C Chakraborty… - ACM Transactions on …, 2024 - dl.acm.org
Epilepsy is one of the significant neurological disorders affecting nearly 65 million people
worldwide. The repeated seizure is characterized as epilepsy. Different algorithms were …

Exploring the intrinsic features of EEG signals via empirical mode decomposition for depression recognition

J Shen, Y Zhang, H Liang, Z Zhao… - … on Neural Systems …, 2022 - ieeexplore.ieee.org
Depression is a severe psychiatric illness that causes emotional and cognitive impairment
and has a considerable impact on patients' thoughts, behaviors, feelings and well-being …

Epileptic seizure detection by cascading isolation forest-based anomaly screening and EasyEnsemble

Y Guo, X Jiang, L Tao, L Meng, C Dai… - … on Neural Systems …, 2022 - ieeexplore.ieee.org
The electroencephalogram (EEG), for measuring the electrophysiological activity of the
brain, has been widely applied in automatic detection of epilepsy seizures. Various EEG …

Seizure onset detection using empirical mode decomposition and common spatial pattern

C Li, W Zhou, G Liu, Y Zhang, M Geng… - … on Neural Systems …, 2021 - ieeexplore.ieee.org
Automatic seizure onset detection plays an important role in epilepsy diagnosis. In this
paper, a novel seizure onset detection method is proposed by combining empirical mode …

Automatic epileptic seizures joint detection algorithm based on improved multi-domain feature of cEEG and spike feature of aEEG

D Wu, Z Wang, L Jiang, F Dong, X Wu, S Wang… - IEEE …, 2019 - ieeexplore.ieee.org
Epilepsy is a disease in which patients undergo seizures caused by brain functionality
disorder. Clinically, it is usually diagnosed by experienced clinicians according to …

Deep long short term memory based minimum variance kernel random vector functional link network for epileptic EEG signal classification

S Parija, R Bisoi, PK Dash, M Sahani - Engineering Applications of Artificial …, 2021 - Elsevier
In this paper, the efficiently extracted and reduced features using deep long short-term
memory (DLSTM) of the epileptic EEG signal integrated with minimum variance kernel …

Epileptic Seizure Detection with an End-to-End Temporal Convolutional Network and Bidirectional Long Short-Term Memory Model.

X Dong, Y Wen, D Ji, S Yuan, Z Liu… - International Journal of …, 2024 - europepmc.org
Automatic seizure detection plays a key role in assisting clinicians for rapid diagnosis and
treatment of epilepsy. In view of the parallelism of temporal convolutional network (TCN) and …

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 …

Time domain implementation of pediatric epileptic seizure detection system for enhancing the performance of detection and easy monitoring of pediatric patients

S Chakrabarti, A Swetapadma, A Ranjan… - … Signal Processing and …, 2020 - Elsevier
Objective The clinical phenomenon of epilepsy varies greatly among patients and this in
turn, has its effect on the quality of life they lead. Studies reveal a requisite for efficient …