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001-es BibID:	BIBFORM090853
035-os BibID:	(Scopus)85090855184
Első szerző:	Sütő József (programtervező informatikus)
Cím:	Music Stimuli Recognition from EEG Signals with EMOTIV EPOC Headset / Jozsef Suto, Zsanett Jambor
Dátum:	2020
ISSN:	1613-0073
Megjegyzések:	It is well-known that, music stimuli have powerful emotion trigger effect. When people listening to music, music induces motor system activities in their brain. Therefore, music can be used as a potential stimulus in electroencephalogram (EEG) based emotion research. The goal of emotion recognition is to explore how different kinds of stimuli (e.g. music) from the world around us influence our brain waves. In previous works, the determination of emotional states has based on subjects' feedback. However, this approach is unreliable almost in all cases because emotional states are changing rather slowly and they are equivocal. In this study we try to recognize musicinduced electroencephalogram patterns by shallow artificial neural network from the popular EMOTIV EPOC+ sensor's signals. This article presents the data acquisition conditions; the efficiency of the neural network with different hyper-parameters; and the effectiveness of EMOTIV EPOC+ over the Neurosky Mindwave device.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok előadáskivonat könyvrészlet
Megjelenés:	Proceedings of the 11th International Conference on Applied Informatics (ICAI 2020) / ed. by Gergely Kovásznai, István Fazekas, Tibor Tómács. - p. 309-317. -
További szerzők:	Jámbor Zsanett (1994-) (mérnök informatikus)
Pályázati támogatás:	EFOP-3.6.3-VEKOP-16-2017-00002 EFOP
Internet cím:	Szerző által megadott URL Intézményi repozitóriumban (DEA) tárolt változat
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