EEG seizure detection and prediction algorithms: a survey
Epilepsy patients experience challenges in daily life due to precautions they have to take in
order to cope with this condition. When a seizure occurs, it might cause injuries or endanger …
order to cope with this condition. When a seizure occurs, it might cause injuries or endanger …
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 automated system for epilepsy detection using EEG brain signals based on deep learning approach
Epilepsy is a life-threatening and challenging neurological disorder, which is affecting a
large number of people all over the world. For its detection, encephalography (EEG) is a …
large number of people all over the world. For its detection, encephalography (EEG) is a …
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 …
Optimized deep neural network architecture for robust detection of epileptic seizures using EEG signals
Objective Automatic detection of epileptic seizures based on deep learning methods
received much attention last year. However, the potential of deep neural networks in seizure …
received much attention last year. However, the potential of deep neural networks in seizure …
[HTML][HTML] One dimensional convolutional neural networks for seizure onset detection using long-term scalp and intracranial EEG
Epileptic seizure detection using scalp electroencephalogram (sEEG) and intracranial
electroencephalogram (iEEG) has attracted widespread attention in recent two decades …
electroencephalogram (iEEG) has attracted widespread attention in recent two decades …
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 …
EEG signal analysis for diagnosing neurological disorders using discrete wavelet transform and intelligent techniques
Analysis of electroencephalogram (EEG) signals is essential because it is an efficient
method to diagnose neurological brain disorders. In this work, a single system is developed …
method to diagnose neurological brain disorders. In this work, a single system is developed …
Epileptic seizure detection: A deep learning approach
Epilepsy is the second most common brain disorder after migraine. Automatic detection of
epileptic seizures can considerably improve the patients' quality of life. Current …
epileptic seizures can considerably improve the patients' quality of life. Current …