Abstract:
The understanding of human emotions for developing applications is a new avenue
in human computer interface. In the Sri Lankan context, military troops and other
individuals involved in war are generally suffering from post-war negative mental
conditions. Although different types of rehabilitation programs are being conducted
currently, brain Computer Interface technology, which was at first used for disabled
people, is used for entertainment, memory capacity improvement, brain activity
development of healthy people. Gaming is one such application of this concept.
Thus, Brain Computer Interface technology could be effectively utilized in the
process of mental rehabilitation for war-affected armed forces and individuals with
emotional control disabilities. In this research, we separate one emotion and use it as
a parameter which was represented in the game. This separated parameter is not
merely a parameter but that logically connect with the real-life characteristics which
will assist to the subjects to control emotions in critical situations. By practicing this
game, subjects will be trained to eliminate negative emotions. Detection of emotions
during gaming is the basic concept behind the mechanism. Using emotions for
therapeutic aspects by training elimination of negative emotions though BCI game
has never been done before. Therefore, previous literature available is relatively less
in this area. In this research we focus on identifying human emotion, anger as the
negative emotion with wireless 16 biosensor EEG head set and use anger driven
game for monitoring the ability to self-control the emotion. Furthermore, statistically
compare efficiency of detecting anger with relatively low electrode number and a
few features. In this paper it is discussed how anger can be separated from the other
closely coupled emotions like frustration and sadness. The results will conclude the
best feature excretion method for emotion separation and the best combination of
electrodes for the emotion, anger. Finally, we statistically analysed the effectiveness
of real time EEG based Game which will help people to identify negative emotions
as quickly as possible when it occurs, and train them to eliminate such blocking
emotions and possibility to use this as a tool to help patients effectively.
