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 …
Transformers in biosignal analysis: A review
Transformer architectures have become increasingly popular in healthcare applications.
Through outstanding performance in natural language processing and superior capability to …
Through outstanding performance in natural language processing and superior capability to …
Performance evaluation of empirical mode decomposition, discrete wavelet transform, and wavelet packed decomposition for automated epileptic seizure detection …
This study proposes a new model which is fully specified for automated seizure onset
detection and seizure onset prediction based on electroencephalography (EEG) …
detection and seizure onset prediction based on electroencephalography (EEG) …
Epileptic seizure detection in EEG signals using a unified temporal-spectral squeeze-and-excitation network
The intelligent recognition of epileptic electro-encephalogram (EEG) signals is a valuable
tool for the epileptic seizure detection. Recent deep learning models fail to fully consider …
tool for the epileptic seizure detection. Recent deep learning models fail to fully consider …
A multivariate approach for patient-specific EEG seizure detection using empirical wavelet transform
Objective: This paper investigates the multivariate oscillatory nature of
electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure …
electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure …
Deep multi-view feature learning for EEG-based epileptic seizure detection
Epilepsy is a neurological illness caused by abnormal discharge of brain neurons, where
epileptic seizure can lead to life-threatening emergencies. By analyzing the encephalogram …
epileptic seizure can lead to life-threatening emergencies. By analyzing the encephalogram …
Detecting epileptic seizures in EEG signals with complementary ensemble empirical mode decomposition and extreme gradient boosting
Epilepsy is a common nervous system disease that is characterized by recurrent seizures.
An electroencephalogram (EEG) records neural activity, and it is commonly used for the …
An electroencephalogram (EEG) records neural activity, and it is commonly used for the …
EEG channel-selection method for epileptic-seizure classification based on multi-objective optimization
We present a multi-objective optimization method for electroencephalographic (EEG)
channel selection based on the non-dominated sorting genetic algorithm (NSGA) for …
channel selection based on the non-dominated sorting genetic algorithm (NSGA) for …
Analysis of high-dimensional phase space via Poincaré section for patient-specific seizure detection
In this paper, the performance of the phase space representation in interpreting the
underlying dynamics of epileptic seizures is investigated and a novel patient-specific seizure …
underlying dynamics of epileptic seizures is investigated and a novel patient-specific seizure …
An efficient method for identification of epileptic seizures from EEG signals using Fourier analysis
Epilepsy is a disease recognized as the chronic neurological dysfunction of the human brain
which is described by the sudden and excessive electrical discharges of the brain cells …
which is described by the sudden and excessive electrical discharges of the brain cells …