A review of epileptic seizure detection using machine learning classifiers

MK Siddiqui, R Morales-Menendez, X Huang… - Brain informatics, 2020 - Springer
Epilepsy is a serious chronic neurological disorder, can be detected by analyzing the brain
signals produced by brain neurons. Neurons are connected to each other in a complex way …

Automated seizure detection using limited-channel EEG and non-linear dimension reduction

J Birjandtalab, MB Pouyan, D Cogan, M Nourani… - Computers in biology …, 2017 - Elsevier
Electroencephalography (EEG) is an essential component in evaluation of epilepsy.
However, full-channel EEG signals recorded from 18 to 23 electrodes on the scalp is neither …

A unified framework and method for EEG-based early epileptic seizure detection and epilepsy diagnosis

Z Chen, G Lu, Z Xie, W Shang - IEEE Access, 2020 - ieeexplore.ieee.org
Electroencephalogram (EEG) contains important physiological information that can reflect
the activity of human brain, making it useful for epileptic seizure detection and epilepsy …

A non-EEG biosignals dataset for assessment and visualization of neurological status

J Birjandtalab, D Cogan, MB Pouyan… - … Workshop on Signal …, 2016 - ieeexplore.ieee.org
Neurological assessment can be used to monitor a person's neurological status. In this
paper, we report collection and analysis of a multimodal dataset of Non-EEG physiological …

Extreme value theory inspires explainable machine learning approach for seizure detection

OE Karpov, VV Grubov, VA Maksimenko, SA Kurkin… - Scientific Reports, 2022 - nature.com
Epilepsy is one of the brightest manifestations of extreme behavior in living systems.
Extreme epileptic events are seizures, that arise suddenly and unpredictably. Usually …

Machine learning based novel cost-sensitive seizure detection classifier for imbalanced EEG data sets

MK Siddiqui, X Huang, R Morales-Menendez… - International Journal on …, 2020 - Springer
Epilepsy is one of the most prevalent neurological disorders. Its accurate detection is a
challenge since sometimes patients do not experience any prior alert to identify a seizure …

An automatic method for epileptic seizure detection based on deep metric learning

L Duan, Z Wang, Y Qiao, Y Wang… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Electroencephalography (EEG) is a commonly used clinical approach for the diagnosis of
epilepsy which is a life-threatening neurological disorder. Many algorithms have been …

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 …

Development of Machine Learning based Epileptic Seizureprediction using Web of Things (WoT)

KKS Liyakat, KP Paradeshi, JA Shaikh… - …, 2022 - search.proquest.com
A significant chronic neurological illness called epilepsy and identified by examining Brain
signals that Brain Neurons' produce. In order to generate messages and communicate with …

ECG-based semi-supervised anomaly detection for early detection and monitoring of epileptic seizures

A Karasmanoglou, M Antonakakis… - International Journal of …, 2023 - mdpi.com
Epilepsy is one of the most common brain diseases, characterized by frequent recurrent
seizures or “ictal” states. A patient experiences uncontrollable muscular contractions …