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

A brain–computer interface (BCI) enables a user to communicate with a computer directly
using brain signals. The most common noninvasive BCI modality, electroencephalogram …

Goal: We present and evaluate a wearable high-density dry-electrode EEG system and an
open-source software framework for online neuroimaging and state classification. Methods …

Brain computer interface technology represents a highly growing field of research with
application systems. Its contributions in medical fields range from prevention to neuronal …

Machine learning is one of the most exciting recent technologies in Artificial Intelligence.
Learning algorithms in many applications that's we make use of daily. Every time a web …

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

Objective. The past two decades have seen dramatic progress in our ability to model brain
signals recorded by electroencephalography, functional near-infrared spectroscopy, etc …

Psychiatric research applications of electroencephalography (EEG), the earliest approach to
imaging human cortical brain activity, are attracting increasing scientific and clinical interest …

Electroencephalography (EEG) holds promise as a neuroimaging technology that can be
used to understand how the human brain functions in real-world, operational settings while …

As the proliferation of technology dramatically infiltrates all aspects of modern life, in many
ways the world is becoming so dynamic and complex that technological capabilities are …