Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Mar 3, 2020
OBJECTIVE: The electroencephalographic (EEG) signals contain information about seizures and their onset location. There are several seizure onset patterns reported in the literature, and these patterns have clinical significance. In this work, we pro...
The diagnosis of psychogenic nonepileptic seizures (PNES) by means of electroencephalography (EEG) is not a trivial task during clinical practice for neurologists. No clear PNES electrophysiological biomarker has yet been found, and the only tool ava...
IEEE journal of biomedical and health informatics
Feb 11, 2020
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 seizure detection approaches strongly rely on patient history records a...
Neural networks : the official journal of the International Neural Network Society
Jan 25, 2020
Recognition of epileptic seizure type is essential for the neurosurgeon to understand the cortical connectivity of the brain. Though automated early recognition of seizures from normal electroencephalogram (EEG) was existing, no attempts have been ma...
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 been studied for decades. Recently, deep learning has been adopted in ord...
Epilepsy is a neurological disorder characterized by sudden and unpredictable epileptic seizures, which incurs significant negative impacts on patients' physical, psychological and social health. A practical approach to assist with the clinical asses...
IEEE transactions on biomedical circuits and systems
Dec 2, 2019
The task of epileptic focus localization receives great attention due to its role in an effective epileptic surgery. The clinicians highly depend on the intracranial EEG data to make a surgical decision related to epileptic subjects suffering from un...
Neural networks : the official journal of the International Neural Network Society
Nov 30, 2019
A deep learning classifier for detecting seizures in neonates is proposed. This architecture is designed to detect seizure events from raw electroencephalogram (EEG) signals as opposed to the state-of-the-art hand engineered feature-based representat...
OBJECTIVE: This research explores absence seizures using data recorded from different layers of somatosensory cortex of four genetic absence epilepsy rats from Strasbourg (GAERS). Localizing the active layers of somatosensory cortex (spatial analysis...
The present study developed a feature selection (FS)-based decision support system using the electroencephalography (EEG) signals recorded from neonates with and without seizures. The study employed 10 different FS algorithms to reduce the classifica...
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