Cognitive neuroscience studies in humans have enabled decades of impactful discoveries
but have primarily been limited to recording the brain activity of immobile participants in a …

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

Motor imagery (MI) based brain–computer interface (BCI) aims to provide a means of
communication through the utilization of neural activity generated due to kinesthetic …

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 …

The ability to recognize errors is crucial for efficient behavior. Numerous studies have
identified electrophysiological correlates of error recognition in the human brain (error …

Brain–computer interfaces (BCIs) are a form of technology that read a user's neural signals
to perform a task, often with the aim of inferring user intention. They demonstrate potential in …

Brain-computer interfaces (BCIs) have been explored in the field of neuroengineering to
investigate how the brain can use these systems to control external devices. We review the …

Objective. Despite the high number of degrees of freedom of the human hand, most actions
of daily life can be executed incorporating only palmar, pincer and lateral grasp. In this study …

The last decade has seen a flowering of applications driven by brain–machine interfaces
(BMIs), particularly brain-actuated robotic devices designed to restore the independence of …

Brain-Computer Interfaces (BCI) are systems that can translate the brain activity patterns of a
user into messages or commands for an interactive application. The brain activity which is …