Latest AI and machine learning research in seizures for healthcare professionals.
PURPOSE: The classification of sleep stages based on Electroencephalogram (EEG) changes has signific...
Electroencephalography (EEG) has demonstrated significant value in diagnosing brain diseases. In par...
Affect recognition in a real-world, less constrained environment is the principal prerequisite of th...
Anthropomorphized robots are increasingly integrated into human social life, playing vital roles acr...
Epilepsy is one of the most well-known neurological disorders globally, leading to individuals exper...
BACKGROUND: Objective and standardized evaluation of surgical skills in robot-assisted surgery (RAS)...
Stroke is a neurological condition that usually results in the loss of voluntary control of body mov...
Differential diagnosis of acute loss of consciousness (LOC) is crucial due to the need for different...
The surging popularity of virtual reality (VR) technology raises concerns about VR-induced motion si...
Due to considerable global prevalence and high recurrence rate, the pursuit of effective new medicat...
. Automated detection of artefact in stimulus-evoked electroencephalographic (EEG) data recorded in ...
This paper proposes a high-accuracy EEG-based schizophrenia (SZ) detection approach. Unlike comparab...
Seizure is a common neurological disorder that usually manifests itself in recurring seizure, and th...
The process of reconstructing underlying cortical and subcortical electrical activities from Electro...
OBJECTIVE: The study presented focuses on the creation of a machine learning (ML) model that uses el...
Neuropsychological studies suggest that co-operative activities among different brain functional are...
The driver in road hypnosis has not only some external characteristics, but also some internal chara...
Epilepsy is one of the most common brain diseases, characterised by repeated seizures that occur on ...
Event-related potentials (ERPs) are cerebral responses to cognitive processes, also referred to as c...
Previous research has primarily employed deep learning models such as Convolutional Neural Networks ...
Brain-computer interface (BCI) technology holds promise for individuals with profound motor impairme...