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

This paper provides a comprehensive overview of the state-of-the-art in brain–computer
interfaces (BCI). It begins by providing an introduction to BCIs, describing their main …

A Brain-Computer Interface (BCI) acts as a communication mechanism using brain signals
to control external devices. The generation of such signals is sometimes independent of the …

To reduce energy consumption and improve residents' quality of life,“smart cities” should
use not only modern technologies, but also the social innovations of the “Internet of …

Attention deficit and hyperactivity disorder (ADHD) have two main characteristics: inattention
and impulsivity. It has many obstacles to the normal development of children and is very …

The goal of this study was to develop a hybrid mental speller that can effectively prevent
unexpected typing errors in the steady-state visual evoked potential (SSVEP)-based mental …

Individual preferences for learning environments can be linked to a specific behavior. The
tendency of such behavior can somehow be associated with an individual's ability to …

The effective decoding of motor imagination EEG signals depends on significant temporal,
spatial, and frequency features. For example, the motor imagination of the single limbs is …

Accessibility, adaptability, and transparency of Brain-Computer Interface (BCI) tools and the
data they collect will likely impact how we collectively navigate a new digital age. This …

Electroencephalography is a non-invasive measure of the brain electrical activity generated
by millions of neurons. Feature extraction in electroencephalography analysis is a core …