Brain-Computer Interfaces (BCIs) translate brain signals into operational commands for technical devices. Different electroencephalogram (EEG) signals have been applied to control a BCI, e.g. slow cortical potentials (SCP), sensorimotor rhythms (SMR) and event-related potentials (ERP).
At University of Würzburg research mainly focuses on two types of EEG signals: SMR and ERP (see also projects).
Brain Computer Interfaces based on modulation of sensory motor rhythms classify differences in EEG patterns during different types of movement imagination (MI) tasks such as hand or foot MI. For example in a typical two-class hand vs. foot MI paradigm these differences enable a BCI user to control an object in a two-dimensional movement environment, for example a computer cursor on a screen. In this case, imagination of hand movement would head the cursor upward; foot MI would head it downward. Hence controlling the cursor would be a balance of two imaginations.
Another type of BCI - the P300-BCI - is based on event related potentials. It is mainly used for communication purpose. Users are presented with a matrix consisting of letters and numbers that are flashed consecutively. By focusing on the intended letter or number, flashing will elicit a prominent positive deflection - the P300 - in the user's EEG. By detecting the P300 from the event related EEG the system is able to identify which letter/number the user is intending to spell. It was shown that users with impaired motor control, e.g. patients suffering from Amyotrophic Lateral Sclerosis (ALS), are able to use the P300-BCI for communication.