An efficient P300-based brain-computer interface for disabled subjects
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At the current stage, Brain-Computer Interfaces (BCIs) represent a promising technology for communication and control of assistive devices as well as for the clinical motor rehabilitation after a stroke. Current BCI systems may be divided in two main typol ...
Objective. A major difficulty of brain–computer interface (BCI) technology is dealing with the noise of EEG and its signal variations. Previous works studied time-dependent non-stationarities for BCIs in which the user's mental task was independent of the ...
A brain-computer interface (BCI) is a system that allows a user to communicate with the environment only through cerebral activity, without using muscular output channels. To establish a direct link between the brain and a computer, the electroencephalogra ...
Feedback stimuli are fundamental components in Brain-Computer Interfaces. It is known that the presentation of feedback stimuli elicits certain brain potentials that can be measured and classified. As stimuli can be given through different sensory modaliti ...
Neurotechnology is the application of scientific knowledge to the practical purpose of understanding, interacting and/or repairing the brain or, in a broader sense, the nervous system. The development of novel approaches to decode functional information fr ...
Recent works have explored the use of brain signals to directly control virtual and robotic agents in sequential tasks. So far in such brain-computer interfaces (BCI), an explicit calibration phase was required to build a decoder that translates raw electr ...
Human studies on cognitive control processes rely on tasks involving sudden-onset stimuli, which allow the analysis of these neural imprints to be time-locked and relative to the stimuli onset. Human perceptual decisions, however, comprise continuous proce ...
Inverse solution allows to estimate sources that generate a given scalp EEG topography. Recently, it has been used in Brain Computer Interfaces (BCIs) to extract robust features based on the hypothesis that projection onto the source space (high dimensiona ...
In this paper we use the cortical current density based inverse solution to classify Event Related Potential, in particular for error-related potential elicited during Brain-Computer Interface experiment. We selected discriminant cortical sources for compa ...
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Brain-machine interfaces (BMIs) have demonstrated how they can be used for reaching tasks with both invasive and non-invasive signal recording methods. Despite the constant improvements in this field, there still exist diverse factors to overcome before ac ...
