Automated epileptic seizure detection in pediatric subjects of CHB-MIT EEG database—a survey
Epilepsy is a neurological disorder of the brain that causes frequent occurrence of seizures.
Electroencephalography (EEG) is a tool that assists neurologists in detecting epileptic …
Electroencephalography (EEG) is a tool that assists neurologists in detecting epileptic …
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 …
include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand …
An EEG based real-time epilepsy seizure detection approach using discrete wavelet transform and machine learning methods
M Shen, P Wen, B Song, Y Li - Biomedical Signal Processing and Control, 2022 - Elsevier
Epilepsy is one of the most common complex brain disorders which is a chronic non-
communicable disease caused by paroxysmal abnormal super-synchronous electrical …
communicable disease caused by paroxysmal abnormal super-synchronous electrical …
Real-time epilepsy seizure detection based on EEG using tunable-Q wavelet transform and convolutional neural network
M Shen, P Wen, B Song, Y Li - Biomedical Signal Processing and Control, 2023 - Elsevier
Epilepsy is a chronic disease caused by sudden abnormal discharge of brain neurons,
leading to transient brain dysfunctions. This paper proposed an EEG based real-time …
leading to transient brain dysfunctions. This paper proposed an EEG based real-time …
Adversarial representation learning for robust patient-independent epileptic seizure detection
Epilepsy is a chronic neurological disorder characterized by the occurrence of spontaneous
seizures, which affects about one percent of the worlds population. Most of the current …
seizures, which affects about one percent of the worlds population. Most of the current …
EEG synchronization analysis for seizure prediction: A study on data of noninvasive recordings
P Detti, G Vatti, G Zabalo Manrique de Lara - Processes, 2020 - mdpi.com
Objective: Epilepsy is a neurological disorder arising from anomalies of the electrical activity
in the brain, affecting~ 65 million individuals worldwide. Prediction methods, typically based …
in the brain, affecting~ 65 million individuals worldwide. Prediction methods, typically based …
Epileptic state classification by fusing hand-crafted and deep learning EEG features
Seizure onset detection and epileptic preictal prediction based on electroencephalogram
(EEG) signals have been a challenge problem in the research community. In this brief, a …
(EEG) signals have been a challenge problem in the research community. In this brief, a …
A robust deep learning approach for automatic classification of seizures against non-seizures
Identifying epileptic seizures through analysis of the electroencephalography (EEG) signal
becomes a standard method for the diagnosis of epilepsy. Manual seizure identification on …
becomes a standard method for the diagnosis of epilepsy. Manual seizure identification on …
[HTML][HTML] Epileptic seizure detection using cross-bispectrum of electroencephalogram signal
Purpose The automatic detection of epileptic seizures in EEG data from extended recordings
can make an important contribution to the diagnosis of epilepsy as it can efficiently reduce …
can make an important contribution to the diagnosis of epilepsy as it can efficiently reduce …
Real-time inference and detection of disruptive EEG networks for epileptic seizures
Recent studies in brain science and neurological medicine paid a particular attention to
develop machine learning-based techniques for the detection and prediction of epileptic …
develop machine learning-based techniques for the detection and prediction of epileptic …