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In-Depth Information
13.4.4 Passive BCI and Virtual Environments
Passive BCI have also been used, but scarcely, in virtual environments and video
games. Several video games that use implicit interaction have been already
developed. Some of them use implicit information to adapt the way the system
responds to commands. It is the case of the game
“
Bacteria Hunt
”
in which the
controllability of the player
is character is impaired by considering the level of alpha
power which is correlated here to relaxed wakefulness (Mhl et al.
2010
).
Some other games adapt the avatar
'
'
s characteristics based on implicit infor-
mation. In
(Bos et al.
2010
, Nijholt et al.
2009
), which is based on
the famous game World of Warcraft, the user
“
AlphaWoW
”
is avatar form is updated (from elf to
wolf) according to the measured level of alpha activity. Another way to use implicit
information for games consists in adapting the game environment (e.g., background
music). Girouard et al. (
2013
) described an experiment in which the user is engaged
in two successive tasks watching a video and playing a Tetris game. The application
was able to predict in which task the user was engaged in, based on measurement of
the brain activity. This allowed to adapt the background music accordingly (e.g.,
increasing tempo). This adaptation was found to lead to a positive impact on user
'
'
s
satisfaction (Girouard et al.
2013
).
Last, some video games can use implicit information to check whether the user
has perceived speci
c game information. In the game developed by Zander et al.
(
2009
), the user has to rotate a letter correctly, as fast as possible. Errors are
introduced by the system. A passive BCI is used to detect whether the user
'
s mental
state reveals that the user has perceived the errors. In this case, the speed of rotation
is increased. A false positive (a perceived error when there is none) slows the
rotation down.
We can notice that these games combine the use of classical devices (e.g.,
keyboard) with a passive BCI. One of them also uses an explicit BCI together with
a passive BCI (Mhl et al.
2010
).
13.5
Conclusion
In this chapter, we proposed an overview of related work on the use of passive BCI
(also named implicit BCI) for interacting with computer applications. We discussed
the de
nition of passive BCI; then, we presented the different brain patterns that
seem to be relevant for this kind of interaction. Finally, we presented the different
applications of passive BCI.
The passive BCI approach holds good potential for BCMI. For instance, the
detection of auditory error response could be used in order to create music systems
that would be aware of the user
'
s perception of music. An other example could be
the evaluation of the user
'
s mental state in order to create or select a musical playlist
that matches the user
'
s emotional state.
