Automatic seizure detection is of great significance for epilepsy diagnosis and alleviating the
massive burden caused by manual inspection of long-term EEG. At present, most seizure …

Epileptic seizure detection using scalp electroencephalogram (sEEG) and intracranial
electroencephalogram (iEEG) has attracted widespread attention in recent two decades …

Automatic seizure detection plays a key role in assisting clinicians for rapid diagnosis and
treatment of epilepsy. In view of the parallelism of temporal convolutional network (TCN) and …

The automatic seizure detection system can effectively help doctors to monitor and diagnose
epilepsy thus reducing their workload. Many outstanding studies have given good results in …

The manual review of an electroencephalogram (EEG) for seizure detection is a laborious
and error-prone process. Thus, automated seizure detection based on machine learning has …

Epilepsy (EP) is a severe neurological disorder characterized by recurrent seizures, which
increases the risk of death three times more than normal. Currently, electroencephalography …

Automatic seizure detection algorithms are necessary for patients with refractory epilepsy.
Many excellent algorithms have achieved good results in seizure detection. Still, most of …

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 …

Seizure detection is a routine process in epilepsy units requiring manual intervention of well-
trained specialists. This process could be extensive, inefficient and time-consuming …

Epileptic seizure detection with multi-channel electroencephalography (EEG) signals is a
commonly used method, but it is tedious and error-prone to manually detect seizures …