IEEE transactions on bio-medical engineering
Aug 17, 2018
OBJECTIVE: We develop an electroencephalography (EEG)-based noninvasive brain-computer interface (BCI) system having short training time (15 min) that can be applied for high-performance control of robotic prosthetic systems.
Machine computer interfaces (MCI) are assistive technologies enabling paralyzed peoples to control and communicate their environments. This study aims to discover and represents a new approach on MCI using left/right motions of voluntary jaw movement...
Medical & biological engineering & computing
Jul 28, 2018
Feature extraction and classification is a vital part in motor imagery-based brain-computer interface (BCI) system. Traditional deep learning (DL) methods usually perform better with more labeled training samples. Unfortunately, the labeled samples a...
Assistive technologies help all persons with disabilities to improve their accessibility in all aspects of their life. The AIDE European project contributes to the improvement of current assistive technologies by developing and testing a modular and ...
A brachial plexus root avulsion (BPRA) causes intractable pain in the insensible affected hands. Such pain is partly due to phantom limb pain, which is neuropathic pain occurring after the amputation of a limb and partial or complete deafferentation....
OBJECTIVE: Brain-computer interfaces (BCI) enable direct communication with a computer, using neural activity as the control signal. This neural signal is generally chosen from a variety of well-studied electroencephalogram (EEG) signals. For a given...
Perceptions, thoughts, and actions unfold over millisecond timescales, while learned behaviors can require many days to mature. While recent experimental advances enable large-scale and long-term neural recordings with high temporal fidelity, it rema...
Computational intelligence and neuroscience
May 15, 2018
Feature of event-related potential (ERP) has not been completely understood and illiteracy problem remains unsolved. To this end, P300 peak has been used as the feature of ERP in most brain-computer interface applications, but subjects who do not sho...
This work aims at corroborating the importance and efficacy of mutual learning in motor imagery (MI) brain-computer interface (BCI) by leveraging the insights obtained through our participation in the BCI race of the Cybathlon event. We hypothesized ...
BACKGROUND: Artificial neural networks (ANNs) are one of the widely used classifiers in the brain-computer interface (BCI) systems-based on noninvasive electroencephalography (EEG) signals. Among the different ANN architectures, the most commonly app...
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