Comparing BCI performance using scalp EEG-and inverse solution-based features
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Non-invasive brain-computer interfaces are traditionally based on mu rhythms, beta rhythms, slow cortical potentials or P300 event-related potentials. However, there is mounting evidence that neural oscillations up to 200 Hz play important roles in process ...
Scalp recorded electroencephalogram signals (EEG) reflect the combined synaptic and axonal activity of groups of neurons. In addition to their clinical applications, EEG signals can be used as support for direct brain-computer communication devices (Brain- ...
High-resolution electroencephalographic (HREEG) techniques allow estimation of cortical activity based on non-invasive scalp potential measurements, using appropriate models of volume conduction and of neuroelectrical sources. In this study we propose an a ...
Brain-computer interfaces (BCIs) aim to provide a new channel of communication by enabling the subject to control an external systems by using purely mental commands. One method of doing this without invasive surgical procedures is by measuring the electri ...
By directly analyzing brain activity, Brain-Computer Interfaces (BCIs) allow for communication that does not rely on any muscular control and therefore constitute a possible communication channel for the completely paralyzed. Typically, the user performs d ...
In recent years a number of non-invasive Brain-Computer Interfaces have been developed that determine the intent of a subject by analysing the Electroencephalograph(EEG) signals up to frequencies of 40Hz. The use of high frequency EEG features have recentl ...
This article raises various issues in the design of an efficient BCI system in multimedia applications. The main focus is on one specific modality, namely an electroencephalography (EEG)-based BCI. In doing so, we provide an overview of the most recent pro ...