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 …

[HTML][HTML] Minireview of epilepsy detection techniques based on electroencephalogram signals

G Liu, R Xiao, L Xu, J Cai - Frontiers in systems neuroscience, 2021 - frontiersin.org
Epilepsy is one of the most common neurological disorders typically characterized by
recurrent and uncontrollable seizures, which seriously affects the quality of life of epilepsy …

RETRACTED: Implementation of deep neural networks for classifying electroencephalogram signal using fractional S‐transform for epileptic seizure detection

SR Ashokkumar, S Anupallavi… - … Journal of Imaging …, 2021 - Wiley Online Library
Epilepsy is one of the most common neurological diseases of the human brain. It affects the
nervous system of brain which shows the impact on an individual's life because of its …

Emotion identification by dynamic entropy and ensemble learning from electroencephalogram signals

SR Ashokkumar, S Anupallavi… - … Journal of Imaging …, 2022 - Wiley Online Library
Emotions are biologically based psychological states brought on by neurophysiologic
changes, variously associated with thoughts, feelings, behavioral responses, and a degree …

Efficient communication and EEG signal classification in wavelet domain for epilepsy patients

SAE El-Gindy, A Hamad, W El-Shafai… - Journal of ambient …, 2021 - Springer
In this paper, we present an approach for the anticipation of electroencephalography (EEG)
seizures using different families of wavelet transform. Different signal attributes are …

An Optimized Neural Network for Content Based Image Retrieval in Medical Applications

GD Flora, G Sekar, R Nivetha… - 2022 8th …, 2022 - ieeexplore.ieee.org
The Content-Based Image Retrieval (CBIR) is a widely used approach for finding and
retrieving related pictures. It is useful in medical applications for detecting disorders like …

[HTML][HTML] Discriminating and understanding brain states in children with epileptic spasms using deep learning and graph metrics analysis of brain connectivity

A Nogales, ÁJ García-Tejedor, P Chazarra… - Computer Methods and …, 2023 - Elsevier
Background and objective Epilepsy is a brain disorder consisting of abnormal electrical
discharges of neurons resulting in epileptic seizures. The nature and spatial distribution of …

[HTML][HTML] Identifying depression disorder using multi-view high-order brain function network derived from electroencephalography signal

F Zhao, T Gao, Z Cao, X Chen, Y Mao… - Frontiers in …, 2022 - frontiersin.org
Brain function networks (BFN) are widely used in the diagnosis of electroencephalography
(EEG)-based major depressive disorder (MDD). Typically, a BFN is constructed by …

Design of an EEG-based transceiver with data decomposition for IoHT applications

M Premkumar, V Jeevanantham… - 2021 Fifth International …, 2021 - ieeexplore.ieee.org
Recently the importance of the Internet of Things (IoT) has opened up the possibility of
developing new applications related to mobile-Health. These include real-time monitoring of …

Epileptic seizure prediction from eigen-wavelet multivariate self-similarity analysis of multi-channel EEG signals

CG Lucas, P Abry, H Wendt… - 2023 31st European …, 2023 - ieeexplore.ieee.org
Epileptic patients may suffer from severe brain damages during seizures. There is thus a
significant need for automated seizure prediction. Independently, brain macroscopic activity …