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Intelligent affective computers can have many medical and non-medical applications. However today's affective computers are limited in scope by their transferability to other application environments or that they monitor only one aspect of physiological emotion expression. Here, the use of a wireless EEG system, which can be implemented in a body area network, is used to investigate the potential of monitoring emotional valence in EEG, for application in real-life situations. The results show 82% accuracy for automatic classification of positive, negative and neutral valence based on film clip viewing, using features containing information on both the frequency content of the EEG and how this changes over time.