Self-supervised Learning with Attention Mechanism for EEG-based seizure detection

T Xiao, Z Wang, Y Zhang, S Wang, H Feng… - … Signal Processing and …, 2024 - Elsevier
Epilepsy is a neurological disorder caused by abnormal brain discharges, which can be
diagnosed by electroencephalography (EEG). Although EEG signals are usually easy to …

Software advancements in automatic epilepsy diagnosis and seizure detection: 10-year review

P Handa, Lavanya, N Goel, N Garg - Artificial Intelligence Review, 2024 - Springer
Epilepsy is a chronic neurological disorder that may be diagnosed and monitored using
routine diagnostic tests like Electroencephalography (EEG). However, manual introspection …

An improved GBSO-TAENN-based EEG signal classification model for epileptic seizure detection

MVVP Kantipudi, NSP Kumar, R Aluvalu… - Scientific Reports, 2024 - nature.com
Detection and classification of epileptic seizures from the EEG signals have gained
significant attention in recent decades. Among other signals, EEG signals are extensively …

Detection Method of Epileptic Seizures Using a Neural Network Model Based on Multimodal Dual-Stream Networks

B Wang, Y Xu, S Peng, H Wang, F Li - Sensors, 2024 - mdpi.com
Epilepsy is a common neurological disorder, and its diagnosis mainly relies on the analysis
of electroencephalogram (EEG) signals. However, the raw EEG signals contain limited …

An efficient epileptic seizure detection by classifying focal and non-focal EEG signals using optimized deep dual adaptive CNN-HMM classifier

PA Chavan, S Desai - Multimedia Tools and Applications, 2024 - Springer
Seizures are defined as short occurrences of unusual elevated brain electrical activity that
can result in a variety of symptoms and actions where Seizures are the main sign of …

Epileptic Seizures Detection Using iEEG Signals and Deep Learning Models

N Abderrahim, A Echtioui, R Khemakhem… - Circuits, Systems, and …, 2024 - Springer
Epilepsy is a common neurological disorder that affects millions of people worldwide, and
many patients do not respond well to traditional anti-epileptic drugs. To improve the lives of …

Electroencephalogram (EEG) Classification using a bio-inspired Deep Oscillatory Neural Network

VS Chakravarthy, S Ghosh, C Vigneswaran, NR Rohan - bioRxiv, 2024 - biorxiv.org
In this paper, we propose two models of oscillatory neural networks the Deep Oscillatory
Neural Network (DONN) and a convolutional variation of it named Oscillatory Convolutional …

African Vultures Based Feature Selection with Multi-modal Deep Learning for Automatic Seizure Prediction

M Nallur, M Sandhya, Z Khan… - 2024 International …, 2024 - ieeexplore.ieee.org
The superiority of life for people with epilepsy can be greatly improved with the assistance of
accurate seizure prediction and early warning. An automatic prediction model is required to …