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 …

The recent advances in pervasive sensing technologies have enabled us to monitor and
analyze the multi-channel electroencephalogram (EEG) signals of epilepsy patients to …

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 affect the patient's physical function and cause irreversible damage to
their brain. It is vital to detect epilepsy seizures in time and give patients antiepileptic …

Automatic seizure detection from electroencephalography (EEG) based on deep learning
has been significantly improved. However, existing works have not adequately excavate the …

The detection of seizures in epileptic patients via Electroencephalography (EEG) is an
essential key to medical treatment. With the advances in deep learning, many approaches …

Automatic seizure detection based on scalp electroencephalogram (EEG) can accelerate
the progress of epilepsy diagnosis. Current seizure detection methods based on deep …

The scalp electroencephalogram (EEG)-based epileptic seizure/nonseizure detection has
been comprehensively studied, and fruitful achievements have been reported in the past …

Epilepsy is a neurological disorder that affects approximately fifty million people according to
the World Health Organization. While electroencephalography (EEG) plays important roles …

Epilepsy is a neurological disorder, and clinicians usually diagnose epilepsy by interpreting
electroencephalogram (EEG) manually. This paper proposes a novel automatic epileptic …