Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …

(1) Background: Chaos, a feature of nonlinear dynamical systems, is well suited for
exploring biological time series, such as heart rates, respiratory records, and particularly …

The understanding of neurophysiological mechanisms responsible for motor imagery (MI) is
essential for the development of brain-computer interfaces (BCI) and bioprosthetics. Our …

We apply artificial neural network (ANN) for recognition and classification of
electroencephalographic (EEG) patterns associated with motor imagery in untrained …

Age-related changes in the human brain functioning crucially affect the motor system,
causing increased reaction time, low ability to control and execute movements, difficulties in …

The development of new approaches to detect motor-related brain activity is key in many
aspects of science, especially in brain–computer interface applications. Even though some …

Research on brain function in natural environments has become a new interest in cognitive
science. In this study, we aim to advance mobile electroencephalography (EEG) participant …

Behavioral experiments evidence that attention is not maintained at a constant level, but
fluctuates with time. Recent studies associate such fluctuations with dynamics of attention …

Epilepsy is a common neurological disease caused by the hypersynchronous discharge of
brain nerve cells. The scalp or intracranial Electroencephalogram (EEG) signals from the …

A nonlinear effect of biological feedback on visual perception is studied when a brain–
computer interface is applied. The implemented algorithm for estimation of visual attention is …