The BCI competition IV stands in the tradition of prior BCI competitions that aim to provide
high quality neuroscientific data for open access to the scientific community. As experienced …

In this paper we review classification algorithms used to design brain–computer interface
(BCI) systems based on electroencephalography (EEG). We briefly present the commonly …

We provide an open access dataset for hybrid brain–computer interfaces (BCIs) using
electroencephalography (EEG) and near-infrared spectroscopy (NIRS). For this, we …

Brain–computer interfaces (BCIs) aim at providing a non-muscular channel for sending
commands to the external world using the electroencephalographic activity or other …

It is widely accepted in the brain computer interface (BCI) research community that
neurological phenomena are the only source of control in any BCI system. Artifacts are …

Interest in develo** a new method of man-to-machine communication-a brain-computer
interface (BCI)-has grown steadily over the past few decades. BCIs create a new …

Brain-computer interfaces (BCIs) are used to translate brain activity signals into control
signals for external devices. Currently, it is difficult for BCI systems to provide the multiple …

For the last few years, many feature extraction methods have been proposed based on
biological signals. Among these, the brain signals have the advantage that they can be …

Non-stationarities are ubiquitous in EEG signals. They are especially apparent in the use of
EEG-based brain–computer interfaces (BCIs):(a) in the differences between the initial …

Background and objective In the brain computer interface (BCI) field, using sub-band
common spatial pattern (SBCSP) and filter bank common spatial pattern (FBCSP) can …