Latest AI and machine learning research in seizures for healthcare professionals.
The paper proposes a new method for deep learning and knowledge discovery in a brain-inspired Spikin...
Epilepsy diagnosis based on Interictal Epileptiform Discharges (IEDs) in scalp electroencephalograms...
The utilization of robotic systems has been increasing in the last decade. This increase has been de...
Emotions composed of cognizant logical reactions toward various situations. Such mental responses st...
This article first studied the morphological characteristics of the EEG for intensive cardiac care; ...
Autism spectrum disorder (ASD) is a developmental disability characterized by persistent impairments...
BACKGROUND AND OBJECTIVE: The detection of brain-related problems and neurological disorders like ep...
The treatment of refractory epilepsy via closed-loop implantable devices that act on seizures either...
The emergence of an aging society is inevitable due to the continued increases in life expectancy an...
This study aimed to produce a novel deep learning (DL) model for the classification of subjects with...
. Noninvasive brain-computer interfaces (BCIs) assist paralyzed patients by providing access to the ...
This paper proposes a novel method and algorithms for the design of MRI structured personalized 3D s...
Currently there are no reliable means of identifying infants at-risk for later language disorders. I...
Electroencephalogram (EEG)-based automated depression diagnosis systems have been suggested for earl...
Early diagnosis of attention deficit and hyperactivity disorder (ADHD) by experts is difficult. Some...
A variety of screening approaches have been proposed to diagnose epileptic seizures, using electroen...
Epilepsy is one of the most common brain disorders worldwide. The most frequently used clinical tool...
As one of the key issues in the field of emotional computing, emotion recognition has rich applicati...
OBJECTIVES: Although Rolandic epilepsy (RE) has been regarded as a brain developmental disorder, neu...
Electroencephalogram (EEG) data, as a kind of complex time-series, is one of the most widely-used in...
Electroencephalography (EEG) microstate analysis is a method wherein spontaneous EEG activity is seg...