Latest AI and machine learning research in seizures for healthcare professionals.
The study reported herein proposes a new method for the diagnosis of epilepsy from electroencephalog...
Automatic seizure detection is of great significance in the monitoring and diagnosis of epilepsy. In...
The spectrum of EEG has been studied to predict the depth of anesthesia using variety of signal proc...
This study presents a novel human-machine interface (HMI) based on both electrooculography (EOG) and...
We carried out a series of statistical experiments to explore the utility of using relevance feedbac...
The development of an innovative functional assessment procedure based on the combination of electro...
OBJECTIVE: To develop a machine learning (ML) methodology based on features extracted from odd-ball ...
The detection of MRI abnormalities that can be associated to seizures in the study of temporal lobe ...
Artificial neural networks (ANNs) effectively analyze non-linear data sets. The aimed was A review o...
OBJECTIVE: Prediction of epileptic seizures can improve the living conditions for refractory epileps...
A better understanding of cortical modifications related to movement preparation and execution after...
Decoding and classification of objects through task-oriented electroencephalographic (EEG) signals a...
Electroencephalography (EEG)-based motor imagery (MI) brain-computer interface (BCI) technology has ...
Feature selection is an important step in many pattern recognition systems aiming to overcome the so...
Background: Selective attention enables the prioritization of behaviorally relevant information in c...
Major depressive disorder (MDD) and other psychiatric diseases can greatly benefit from objective de...
Reconstructing speech envelopes from electroencephalography(EEG) signals is a challenging but valuab...
Hibernating bears show remarkable metabolic suppression. Their decline in core body temperature (Tb)...
Background and Purpose: Drug resistant epilepsy (DRE) affects approximately 15 million people worldw...
Background. This study examines a competition based model (Cmodel) designed to capture the temporal ...
While Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in general v...