Music Stimuli Recognition in Electroencephalogram Signal

Authors

  • Jozsef Suto
  • Stefan Oniga

DOI:

https://doi.org/10.5755/j01.eie.24.4.21482

Keywords:

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

Abstract

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.

DOI: http://dx.doi.org/10.5755/j01.eie.24.4.21482

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Published

2018-08-20

How to Cite

Suto, J., & Oniga, S. (2018). Music Stimuli Recognition in Electroencephalogram Signal. Elektronika Ir Elektrotechnika, 24(4), 68-71. https://doi.org/10.5755/j01.eie.24.4.21482

Issue

Vol. 24 No. 4 (2018)

Section

SYSTEM ENGINEERING, COMPUTER TECHNOLOGY

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