A review of epileptic seizure detection using machine learning classifiers
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 …
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
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 …
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 **e, 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 …
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
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 …
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
Epilepsy is one of the brightest manifestations of extreme behavior in living systems.
Extreme epileptic events are seizures, that arise suddenly and unpredictably. Usually …
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
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 …
challenge since sometimes patients do not experience any prior alert to identify a seizure …
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 …
to study the electrical activity of the human brain. The machine learning-based classifier is …
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 …
epilepsy which is a life-threatening neurological disorder. Many algorithms have been …
ECG-based semi-supervised anomaly detection for early detection and monitoring of epileptic seizures
Epilepsy is one of the most common brain diseases, characterized by frequent recurrent
seizures or “ictal” states. A patient experiences uncontrollable muscular contractions …
seizures or “ictal” states. A patient experiences uncontrollable muscular contractions …
Development of Machine Learning based Epileptic Seizureprediction using Web of Things (WoT)
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 …
signals that Brain Neurons' produce. In order to generate messages and communicate with …