Advances in brain-computer interface (BCI) technology have facilitated the detection of
Motor Imagery (MI) from electroencephalography (EEG). First, we present three strategies of …

Due to the volume conduction multichannel electroencephalogram (EEG) recordings give a
rather blurred image of brain activity. Therefore spatial filters are extremely useful in single …

Objective: This paper tackles the problem of transfer learning in the context of
electroencephalogram (EEG)-based brain-computer interface (BCI) classification. In …

Electroencephalograms (EEGs) are becoming increasingly important measurements of
brain activity and they have great potential for the diagnosis and treatment of mental and …

A Brain-Computer Interface (BCI) is a specific type of human-computer interface that enables
the direct communication between human and computers by analyzing brain …

Theory, algorithms, and applications of machine learning techniques to overcome “covariate
shift” non-stationarity. As the power of computing has grown over the past few decades, the …

This paper describes the OpenViBE software platform which enables researchers to design,
test, and use brain–computer interfaces (BCIs). BCIs are communication systems that …

A common assumption in supervised learning is that the input points in the training set follow
the same probability distribution as the input points that will be given in the future test phase …

Brain–Computer Interface (BCI) systems establish a direct communication channel from the
brain to an output device. These systems use brain signals recorded from the scalp, the …

The possibility of speech processing in the absence of an intelligible acoustic signal has
given rise to the idea of a 'silent speech'interface, to be used as an aid for the speech …