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 …

Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from
neurophysiology, computer science, and engineering in an effort to establish real-time …

Objective. Signal classification is an important issue in brain computer interface (BCI)
systems. Deep learning approaches have been used successfully in many recent studies to …

Brain–computer interfaces (BCIs) use brain activity to control external devices, thereby
enabling severely disabled patients to interact with the environment. A variety of invasive …

Emotion classification based on brain–computer interface (BCI) systems is an appealing
research topic. Recently, deep learning has been employed for the emotion classifications of …

People with severe neurological impairments face many challenges in sensorimotor
functions and communication with the environment; therefore they have increased demand …

A brain-computer interface (BCI) is a hardware and software communications system that
permits cerebral activity alone to control computers or external devices. The immediate goal …

Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them
into commands that are relayed to output devices that carry out desired actions. BCIs do not …

Over the past several decades, electroencephalogram (EEG)-based brain-computer
interfaces (BCIs) have attracted attention from researchers in the field of neuroscience …

Damage or degeneration of motor pathways necessary for speech and other movements, as
in brainstem strokes or amyotrophic lateral sclerosis (ALS), can interfere with efficient …