The electroencephalogram (EEG) signal in the brain–computer interface (BCI) has suffered
great cross-subject variability. The BCI system needs to be retrained before each time it is …

Within data-driven artificial intelligence (AI) systems for industrial applications, ensuring the
reliability of the incoming data streams is an integral part of trustworthy decision-making. An …

Predicting a subject's ability to use a Brain Computer Interface (BCI) is one of the major
issues in the BCI domain. Relevant applications of forecasting BCI performance include the …

Brain Computer Interfaces suffer from considerable cross-session and cross-subject
variability, which makes it hard for classification methods to generalize. We introduce a …

Objective. Brain-computer interfaces (BCI) based on event-related potentials (ERP)
incorporate a decoder to classify recorded brain signals and subsequently select a control …

Introduction Motor Brain–Computer Interfaces (BCIs) create new communication pathways
between the brain and external effectors for patients with severe motor impairments. Control …

Brain-computer interfaces (BCIs) transform neural signals into commands for effectors. They
are mainly used as tools for functional compensation of impaired functions in disabled …

Non-invasive Brain Computer Interfaces (BCIs) allow a user to control a machine using only
their brain activity. The BCI system acquires electroencephalographic (EEG) signals …

Brain-computer interfaces (BCIs) are systems that allow the control of external devices from
the brain's neural signals without neuromuscular activation. Among the various applications …

Les interfaces cerveau machine (BCI pour Brain Computer Interfaces) non invasives
permettent à leur utilisateur de contrôler une machine par la pensée. Ce dernier doit porter …