Social Environments, Mixed Communication and Goal-Oriented Control Application Using a Brain-Computer Interface

For this study a P300 BCI speller application framework served as a base to explore the operation for three different applications. Subjects exchanged messages in the networks of (i) Twitter (Twitter Inc.) and socialized with other residents in Second Life (Linden Lab) and (ii) controlled a virtual smart home. Although the complexity of the various applications varied greatly, all three applications yielded similar results which are interesting for the general application of BCI for communication and control: (a) icons can be used together with characters in the interface masks and (b) more crucially, the BCI system does not need to be trained on each individual symbol and allows the use of icons for many different tasks without prior time consuming and boring training for each individual icon. Hence such a type of BCI system is more optimally suited for goal oriented control amongst currently available BCI systems.