Brain–Computer Interfaces - Index of

88 G. Pfurtscheller et al.
differences, only a trend, these findings, consistent over all types of spatial filters,
suggest that foot MI in combination with hand MI is a good choice when working
with naive BCI users the first time. Frequency components between 10–14 Hz
(upper mu components) are induced frequently in the hand representation area (mu
ERS) during foot MI and proved to be very important to achieve high classification
accuracies [37].
6 Special Applications of the Graz BCI
Three applications are reported. The first two applications involve control of immersive
virtual environments, and the third application let users operate Google Earth
through thought.
6.1 Self-Paced Exploration of the Austrian National Library
An interesting question is whether it is possible to navigate through a complex
Virtual Environment (VE) without using any muscle activity, such as speech and
limb movement. Here we report on an experiment in the Graz DAVE (Definitely
Affordable Virtual Environment [15]). The goal of this experiment was to walk (selfpaced)
through a model of the Austrian National Library (see Fig. 6a) presented
in the DAVE with three rear-projected active stereo screens and a front-projected
screen on the floor.
Subjects started with a cue-based BCI training with 2 MI classes. During this
training they learned to establish two different brain patterns by imagining hand or
foot movements (for training details see [24, 31]). After offline LDA output analysis,
the MI which was not preferred (biased) by the LDA was selected for self-paced
training. Each time the LDA output exceeded a selected threshold for a predefined
dwell time [65], the BCI replied to the DAVE request with a relative coordinate
change. Together with the current position of the subject within the VE and the
tracking information of the subject’s head (physical movements), the new position
within the VE was calculated. The whole procedure resulted in a smart forward
movement through the virtual library whenever the BCI detected the specified MI.
For further details see [25].
The task of the subject within the VE was to move through MI towards the end
of the main hall of the Austrian National Library along a predefined pathway. The
subject started at the entrance door and had to stop at five specific points. The experiment
was divided in 5 activity times (movement through thought) and 5 pause times
(no movement). After a variable pause time of approximately 1 min, the experimenter
gave a command (“experimenter-based”) and subject started to move as fast
as possible towards the next point. From the 5 activity and 5 pause times, the true
positives (TP, correct moving) and false negatives (FN, periods of no movement