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 …

Objective. Most current electroencephalography (EEG)-based brain–computer interfaces
(BCIs) are based on machine learning algorithms. There is a large diversity of classifier …

Brain-computer interfaces (BCI) are used in stroke rehabilitation to translate brain signals
into intended movements of the paralyzed limb. However, the efficacy and mechanisms of …

Brain-computer interface (BCI) technologies aim to provide a bridge between the human
brain and external devices. Prior research using non-invasive BCI to control virtual objects …

Over the past decade, many researchers have come up with different implementations of
systems for decoding covert or imagined speech from EEG (electroencephalogram). They …

The performance of brain-computer interfaces (BCIs) improves with the amount of available
training data; the statistical distribution of this data, however, varies across subjects as well …

EEG is the recording of electrical activities of the brain, usually along the scalp surface,
which are the results of synaptic activations of the brain's neurons. In recent years, it has …

Removal of motion artifacts is a critical challenge, especially in wearable
electroencephalography (EEG) and photoplethysmography (PPG) devices that are exposed …

Brain-computer interface (BCI)) research seeks to develop new augmentative
communication and control technology for human patients with severe neuromuscular …

Many laboratories have begun to develop brain-computer interface (BCI) systems that
provide communication and control capabilities to people with severe motor disabilities …