Detecting epileptic seizure with different feature extracting strategies using robust machine learning classification techniques by applying advance parameter …

L Hussain - Cognitive neurodynamics, 2018 - Springer
Epilepsy is a neurological disorder produced due to abnormal excitability of neurons in the
brain. The research reveals that brain activity is monitored through electroencephalogram …

Detection of epileptic seizure from EEG signal data by employing machine learning algorithms with hyperparameter optimization

AA Rahman, F Faisal, MM Nishat… - … Conference on Bio …, 2021 - ieeexplore.ieee.org
Epileptic seizure refers to a brief occurrence of signs in the brain caused by abnormally high
or synchronized neuronal activity. With the utilization of EEG signal, the epileptic seizure can …

Detection of epileptic seizures through EEG signals using entropy features and ensemble learning

M Dastgoshadeh, Z Rabiei - Frontiers in human neuroscience, 2023 - frontiersin.org
Introduction Epilepsy is a disorder of the central nervous system that is often accompanied
by recurrent seizures. World health organization (WHO) estimated that more than 50 million …

Application of machine learning in epileptic seizure detection

LV Tran, HM Tran, TM Le, TTM Huynh, HT Tran… - Diagnostics, 2022 - mdpi.com
Epileptic seizure is a neurological condition caused by short and unexpectedly occurring
electrical disruptions in the brain. It is estimated that roughly 60 million individuals worldwide …

[HTML][HTML] Electroencephalogram signal classification for automated epileptic seizure detection using genetic algorithm

BS Nanthini, B Santhi - Journal of natural science, biology, and …, 2017 - ncbi.nlm.nih.gov
Background: Epilepsy causes when the repeated seizure occurs in the brain.
Electroencephalogram (EEG) test provides valuable information about the brain functions …

Epilepsy detection in EEG signal using recurrent neural network

I Aliyu, YB Lim, CG Lim - Proceedings of the 2019 3rd International …, 2019 - dl.acm.org
In this paper, we proposed a Recurrent Neural Network (RNN) for the classification of
epileptic EEG signal. The EEG dataset is first preprocessed using Discrete Wavelet …

Automatic epileptic seizure detection using MSA-DCNN and LSTM techniques with EEG signals

M Anita, AM Kowshalya - Expert Systems with Applications, 2024 - Elsevier
To identify epilepsy, Electroencephalography (EEG) is an important and common tool used
to study the electrical activity of the human brain. The machine learning-based classifier is …

Evaluating the window size's role in automatic EEG epilepsy detection

V Christou, A Miltiadous, I Tsoulos, E Karvounis… - Sensors, 2022 - mdpi.com
Electroencephalography is one of the most commonly used methods for extracting
information about the brain's condition and can be used for diagnosing epilepsy. The EEG …

An automated detection of epileptic seizures EEG using CNN classifier based on feature fusion with high accuracy

W Chen, Y Wang, Y Ren, H Jiang, G Du… - BMC Medical informatics …, 2023 - Springer
Background Epilepsy is a neurological disorder that is usually detected by
electroencephalogram (EEG) signals. Since manual examination of epilepsy seizures is a …

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 …