Motor Imagery Brain-Computer Interfaces (MI-BCIs) are AI-driven systems that capture brain
activity patterns associated with mental imagination of movement and convert them into …

Brain-machine interface (BMI) systems have been widely studied to allow people with motor
paralysis conditions to control assistive robotic devices that replace or recover lost function …

We present a literature review and a toolbox to help the reader find the best method to
design for and assess Sense of Embodiment (SoE) in several application scenarios. The …

Brain–computer interfaces (BCIs) are systems that enable a person to interact with a
machine using only neural activity. Such interaction can be non-intuitive for the user hence …

Brain-computer interfaces (BCIs) are communication bridges between a human brain and
external world, enabling humans to interact with their environment without muscle …

Motor Imagery BCI systems have a high rate of users that are not capable of modulating their
brain activity accurately enough to communicate with the system. Several studies have …

Error-related potentials (ErrPs) are the neural signature of error processing. Therefore, the
detection of ErrPs is an intuitive approach to improve the performance of brain-computer …

Kinesthetic motor imagery (KMI) generates specific brain patterns in sensorimotor rhythm
over the motor cortex (called event-related (de)-synchronization, ERD/ERS), allowing KMI to …

The motor imagery (MI)-based brain computer interface (BCI) is an intuitive interface that
enables users to communicate with external environments through their minds. However …

Brain computer interfaces (BCIs) have been developed and implemented in many areas as
a new communication channel between the human brain and external devices. Despite their …