Ricerc@Sapienza

Human computer interface (HCI) has become more and more important in the last few years. This is mainly due to the increase in the technology and in the new possibilities in yielding a help to disabled people. Brain Computer Interfaces (BCI) represent a subset of the HCI systems which use measurements of the voluntary brain activity for driving a communication system mainly useful for severely disabled people. Electroencephalography (EEG) has been intensively used for the measurement of electrical signals related to the brain activity.

Introduction Modern neuroimaging has provided unequivocal evidence that brain functions are
subserved by multiple areas functionally interconnected. Brain computer interfaces (BCIs) may benefit
from feature extraction based on metrics derived from brain connectivity [1]-[3]. However, reaching the
minimally required accuracy when few data samples are available as in single trial or real-time
connectivity applications is still challenging. Variables selection algorithms could represent a valuable