Music Stimuli Recognition in Electroencephalogram Signal

Jozsef Suto, Stefan Oniga


When humans are listening to music they perceive beats, rhythms and melodies. Music stimuli induce motor system activities and it has a powerful emotion trigger effect. Since music is a potential stimulus in electroencephalogram based emotion research we supposed that different kinds of songs are recognizable from electroencephalogram signal. In this study we try to recognize music-induced electroencephalogram responses with the popular Neurosky Mindwave device. This paper describes the test conditions and the efficiency of an artificial neural network in combination with different data pre-processing techniques. The final outcomes show the negative effect of frequency decomposition and that the meditation level has more significant effect on the recognition than a particular song.



Artificial neural networks; Brain-computer interfaces; Digital filtering; Electroencephalography.

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Print ISSN: 1392-1215
Online ISSN: 2029-5731