A flexible brain-computer interface

Recent advances in computer hardware and signal processing have made it feasible to use human EEG signals or “brain waves” to communicate with a computer. Locked-in patients now have a means to communicate with the outside world. Even with modern advances, such systems still suffer from communication rates on the order of 2–3 items/minute. In addition, existing systems are not likely to be designed with flexibility in mind, leading to slow systems that are difficult to improve. This dissertation presents a flexible brain-computer interface that is designed to facilitate changes in signal processing methods and user applications. In order to show the flexibility of the system, several applications, ranging from a brain-body actuated video game played with eye movements to a brain-computer interface for environmental control in a virtual apartment, are shown.; The P3 evoked potential is a positive wave in the EEG signal peaking at around 300 milliseconds after task-relevant stimuli and it can be used as a binary control signal. A virtual driving experiment shows that the P3 can be reliably detected within a virtual environment. Several on-line algorithms for processing single trial P3 evoked potentials are presented and compared. It is important that actual EEG signals rather than signal artifacts are being recognized and thus false recognition of artifacts is shown to be small.; Results from an environmental control application within a virtual apartment are presented. Subjects do not perform significantly different between controlling the application from a computer monitor and when fully immersed in the virtual apartment and subjects like the immersive VR environment better. This highlights the fact that the P3 component of the evoked potential is robust over different environments and that usability does not depend solely on performance, but on other factors as well. Future work is discussed within this context.