Brain-computer interfaces (BCI) are communication system that use brain activities to control a device. The BCI studied is based on the P300 speller [1]. A new algorithm to select relevant sensors is proposed: it is based on a previous proposed algorithm [2] used to enhance P300 potentials by spatial filters. Data recorded on three subjects were used to evaluate the proposed selection method: i...

Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands that are relayed to output devices that carry out desired actions. BCIs do not use normal neuromuscular output pathways. The main goal of BCI is to replace or restore useful function to people disabled by neuromuscular disorders such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or...

Using Machine Learning and Deep to predict cognitive tasks from electroencephalography (EEG) signals is a rapidly advancing field in Brain-Computer Interfaces (BCI). In contrast the fields of computer vision natural language processing, data amount these trials still rather tiny. Developing PC-based machine learning technique increase participation non-expert end-users could help solve this col...

1 Brain–computer interfaces (BCIs) aim at providing a non-muscular channel 2 for sending commands to the external world using brain activity. Most 3 existing BCIs detect specific mental activity in a so-called synchronous 4 paradigm. Unlike synchronous systems that are operational at specific 5 system-defined periods, self-paced interfaces have the advantage of being 6 operational at all times....

Abstract Recent advancements in magnetoencephalography (MEG)-based brain-computer interfaces (BCIs) have shown great potential. However, the performance of current MEG-BCI systems is still inadequate and one main reasons for this unavailability open-source datasets. MEG are expensive hence datasets not readily available researchers to develop effective efficient BCI-related signal processing al...

Advances in neural interfaces have demonstrated remarkable results in the direction of replacing and restoring lost sensorimotor function in human patients. Noninvasive brain-computer interfaces (BCIs) are popular due to considerable advantages including simplicity, safety, and low cost, while recent advances aim at improving past technological and neurophysiological limitations. Taking into ac...

Brain-Computer Interface (BCI) is a way to control computers by using human brain waves. As the technology has improved, BCI devices have become smaller and cheaper, making it possible for more individuals to buy them. This allows BCI to be applied to new fields outside of pure research, including entertainment. We examine whether BCI devices can be used as a new gaming device, approaching it f...

Technologies of the current era provide the ability to interface and communicate directly from one human brain to another. This can be done by using Transcranial magnetic stimulation (TMS), Brain to Brain Interfaces (BBIs), EEG (electroencephalograph) and the Internet. Computer commands are generated using the brain-to-computer interface (BCI) and these commands are translated to generate brain...

Movement-based brain–computer Interfaces (BCI) rely significantly on the automatic identification of movement intent. They also allow patients with motor disorders to communicate external devices. The extraction and selection discriminative characteristics, which often boosts computer complexity, is one issues automatically discovered intentions. This research introduces a novel method for cate...