Brain Computer Interfaces Employing Machine Learning Methods : A Systematic Review

Machine learning methods for brain computer interfaces

Machine Learning Techniques for Brain-computer Interfaces

This review discusses machine learning methods and their application to Brain-Computer Interfacing. A particular focus is placed on feature selection. We also point out common flaws when validating machine learning methods in the context of BCI. Finally we provide a brief overview on the Berlin-Brain Computer Interface (BBCI).

Brain Computer Interfaces , a review

The brain is in many respects the centre of our being, controlling our actions, movements, thoughts and emotions. It is somewhat of a mystery, presenting itself only through the body's exterior façade. It is safeguarded by a thick skull that insulates it from the outside world. Information from the surroundings is relayed to it via the five senses touch, sight, sound, smell and taste. Its role ...

Brain Computer Interfaces, a Review

A brain-computer interface (BCI) is a hardware and software communications system that permits cerebral activity alone to control computers or external devices. The immediate goal of BCI research is to provide communications capabilities to severely disabled people who are totally paralyzed or 'locked in' by neurological neuromuscular disorders, such as amyotrophic lateral sclerosis, brain stem...

Brain-machine and brain-computer interfaces.

The idea of connecting the human brain to a computer or machine directly is not novel and its potential has been explored in science fiction. With the rapid advances in the areas of information technology, miniaturization and neurosciences there has been a surge of interest in turning fiction into reality. In this paper the authors review the current state-of-the-art of brain-computer and brain...