Combining Inter-Subject Modeling with a Subject-Based Data Transformation to Improve Affect Recognition from EEG Signals

Existing correlations between features extracted from Electroencephalography (EEG) signals and emotional aspects have motivated the development of a diversity of EEG-based affect detection methods. Both intra-subject and inter-subject approaches have been used in this context. Intra-subject approach...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 19; no. 13; p. 2999
Main Authors:	Arevalillo-Herráez, Miguel, Cobos, Maximo, Roger, Sandra, García-Pineda, Miguel
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 08.07.2019 MDPI
Subjects:	Algorithms Arousal - physiology arousal detection Artificial intelligence Biometric identification Biometrics Data Analysis data transformation Databases, Factual EEG Electroencephalography Electroencephalography - methods Emotions Emotions - physiology Fourier transforms Humans Information sources International conferences Machine learning Methods Models, Biological normalization Physiology Signal processing Signal Processing, Computer-Assisted Support Vector Machine valence detection Wavelet transforms arousal detection valence detection data transformation normalization EEG
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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