IEEE transactions on bio-medical engineering
Nov 12, 2014
This study presents a novel human-machine interface (HMI) based on both electrooculography (EOG) and electroencephalography (EEG). This hybrid interface works in two modes: an EOG mode recognizes eye movements such as blinks, and an EEG mode detects ...
We carried out a series of statistical experiments to explore the utility of using relevance feedback on electroencephalogram (EEG) data to distinguish between different activity states in human absence epilepsy. EEG recordings from 10 patients with ...
The development of an innovative functional assessment procedure based on the combination of electroencephalography (EEG) and robot-assisted upper limb devices may provide new insights into the dynamics of cortical reorganization promoted by rehabili...
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Aug 27, 2014
OBJECTIVE: To develop a machine learning (ML) methodology based on features extracted from odd-ball auditory evoked potentials to identify neurophysiologic changes induced by Clozapine (CLZ) treatment in responding schizophrenic (SCZ) subjects. This ...
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Jun 4, 2014
OBJECTIVE: Prediction of epileptic seizures can improve the living conditions for refractory epilepsy patients. We aimed to improve sensitivity and specificity of prediction methods, and to reduce the number of false alarms.
A better understanding of cortical modifications related to movement preparation and execution after robot-assisted training could aid in refining rehabilitation therapy protocols for stroke patients. Electroencephalography (EEG) modifications of cor...
Decoding and classification of objects through task-oriented electroencephalographic (EEG) signals are the most crucial goals of recent researches conducted mainly for brain-computer interface applications. In this study we aimed to classify single-t...
Electroencephalography (EEG)-based motor imagery (MI) brain-computer interface (BCI) technology has the potential to restore motor function by inducing activity-dependent brain plasticity. The purpose of this study was to investigate the efficacy of ...
Feature selection is an important step in many pattern recognition systems aiming to overcome the so-called curse of dimensionality. In this study, an optimized classification method was tested in 147 patients with major depressive disorder (MDD) tre...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.