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Nowadays, many people suffer from negative moods like sadness or anxiety. As an effective tool to relieve such moods, music therapy is widely embraced. Furthermore, researchers try to use newly developed bio-feedback technologies like electroencephalograms (EEG) to measure the effects of music therapy since it can reflect people's emotion sensitively and objectively. In this paper, we design a mobile platform of music therapy based on EEG feedback. The platform can record user's EEG in real time, analyze the emotion state, and choose a suitable music track to play. Users can adjust their emotion at anytime and anywhere. They can examine the therapeutic effects in time by observing EEG feedback on mobile client. In consideration of the hardware and software resources of mobile device limitations, we only collect EEG data from two channels and barely compute beta/alpha power ratio and alpha lateralization as the signal features used to measure test subjects' emotion status. Accordingly, we've committed experiments involving 4 subjects. Preliminary results show that the prototype design of the music therapy is fitful and it can be used in the mobile platform because of its simplicity and accuracy.
Date of Conference: 1-3 Dec. 2010