Support vector machines (SVMs) are widely used classifiers for detecting physiological
patterns in human–computer interaction (HCI). Their success is due to their versatility …

Objective. Stroke is one of the most common neural disorders, which causes physical
disabilities and motor impairments among its survivors. Several technologies have been …

In this work, we propose a novel brain-controlled wheelchair, one of the major applications
of brain-machine interfaces (BMIs), that allows an individual with mobility impairments to …

Abstract Brain-Computer Interface (BCI) or Human-Machine Interface now becoming vital
biomedical engineering and technology field which applying EEG technologies to provide …

Brain-computer interface (BCI) is a novel human-computer interaction model, which does
not depend on the conventional output pathway (peripheral nerve and muscle tissue). In the …

Brain–computer interfaces (BCIs) based on steady-state visually evoked potentials
(SSVEPs) have been well researched due to their easy system configuration, little or no user …

Electroencephalogram (EEG) signals can be used to capture the electrical pattern
generated on the surface of the human brain. The electrical activity in terms of EEG signals …

Hybrid brain computer interfaces (hBCIs) have emerged as a possible path to integrated
brain-computer interaction in current history. hBCI, is a device formed by the amalgamation …

In this work, we address the problem of integrating a robotic wheelchair into a smart
environment. This approach allows people with disabilities to control home appliances of the …

Electroencephalogram‐(EEG‐) based brain‐computer interface (BCI) systems usually utilize
one type of changes in the dynamics of brain oscillations for control, such as event‐related …