Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices
through the utilization of brain waves. It is worth noting that the application of BCI is not only …

Advances in brain science and computer technology in the past decade have led to exciting
developments in brain–computer interface (BCI), thereby making BCI a top research area in …

Patients with amyotrophic lateral sclerosis (ALS) can lose all muscle-based routes of
communication as motor neuron degeneration progresses, and ultimately, they may be left …

Over the last few decades, the Brain-Computer Interfaces have been gradually making their
way to the epicenter of scientific interest. Many scientists from all around the world have …

Brain–computer interfaces (BCIs) use brain activity to control external devices, thereby
enabling severely disabled patients to interact with the environment. A variety of invasive …

Abstract Brain Computer Interface (BCI) is defined as a combination of hardware and
software that allows brain activities to control external devices or even computers. The …

Abstract Background and Objective Using deep-learning methodologies to analyze
multimodal physiological signals becomes increasingly attractive for recognizing human …

Digital signal processing of electroencephalography (EEG) data is now widely utilized in
various applications, including motor imagery classification, seizure detection and …

Digital processing of electroencephalography (EEG) signals has now been popularly used
in a wide variety of applications such as seizure detection/prediction, motor imagery …

Successful applications of brain-computer interface (BCI) approaches to motor imagery (MI)
are still limited. In this paper, we propose a classification framework for MI …