Applications of artificial intelligence in automatic detection of epileptic seizures using EEG signals: A review

S Saminu, G Xu, S Zhang… - Artificial Intelligence …, 2023 - ojs.bonviewpress.com
Correctly interpreting an Electroencephalography (EEG) signal with high accuracy is a
tedious and time-consuming task that may take several years of manual training due to its …

Theoretical and methodological analysis of EEG based seizure detection and prediction: An exhaustive review

R Cherian, EG Kanaga - Journal of neuroscience methods, 2022 - Elsevier
Epilepsy is a chronic neurological disorder with a comparatively high prevalence rate. It is a
condition characterized by repeated and unprovoked seizures. Seizures are managed with …

Machine learning and deep learning approach for medical image analysis: diagnosis to detection

M Rana, M Bhushan - Multimedia Tools and Applications, 2023 - Springer
Computer-aided detection using Deep Learning (DL) and Machine Learning (ML) shows
tremendous growth in the medical field. Medical images are considered as the actual origin …

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 …

Electroencephalogram signal classification based on Fourier transform and Pattern Recognition Network for epilepsy diagnosis

Q Gao, AH Omran, Y Baghersad, O Mohammadi… - … Applications of Artificial …, 2023 - Elsevier
Epilepsy is a central nervous system (CNS) disorder that affects nerve cells in the brain and
produces seizures in which consciousness is lost. People with epilepsy have frequent …

Feature engineering of EEG applied to mental disorders: a systematic map** study

S García-Ponsoda, J García-Carrasco, MA Teruel… - Applied …, 2023 - Springer
Around a third of the total population of Europe suffers from mental disorders. The use of
electroencephalography (EEG) together with Machine Learning (ML) algorithms to diagnose …

Deep convolutional neural network regularization for alcoholism detection using EEG signals

H Mukhtar, SM Qaisar, A Zaguia - Sensors, 2021 - mdpi.com
Alcoholism is attributed to regular or excessive drinking of alcohol and leads to the
disturbance of the neuronal system in the human brain. This results in certain malfunctioning …

[HTML][HTML] Epileptic seizure detection from electroencephalogram (EEG) signals using linear graph convolutional network and DenseNet based hybrid framework

FA Jibon, MH Miraz, MU Khandaker, M Rashdan… - Journal of Radiation …, 2023 - Elsevier
A clinical condition known as epilepsy occurs when the brain's regular electrical activity is
disturbed, resulting in a rapid, aberrant, and excessive discharge of brain neurons. The …

Common spatial pattern-based feature extraction and worm gear fault detection through vibration and acoustic measurements

YE Karabacak, NG Özmen - Measurement, 2022 - Elsevier
Condition monitoring is a major part of predictive maintenance which monitors a particular
condition in machinery to identify changes that could indicate a develo** fault. It allows …

Epileptic seizure classification based on random neural networks using discrete wavelet transform for electroencephalogram signal decomposition

SY Shah, H Larijani, RM Gibson, D Liarokapis - Applied Sciences, 2024 - mdpi.com
An epileptic seizure is a brief episode of symptoms and signs caused by excessive electrical
activity in the brain. One of the major chronic neurological diseases, epilepsy, affects …