Emotional state classification from EEG data using machine learning approach

Recently, emotion classification from EEG data has attracted much attention with the rapid development of dry electrode techniques, machine learning algorithms, and various real-world applications of brain–computer interface for normal people. Until now, however, researchers had little understanding...

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Bibliographic Details
Published in:	Neurocomputing (Amsterdam) Vol. 129; pp. 94 - 106
Main Authors:	Wang, Xiao-Wei, Nie, Dan, Lu, Bao-Liang
Format:	Journal Article Conference Proceeding
Language:	English
Published:	Amsterdam Elsevier B.V 10.04.2014 Elsevier
Subjects:	Applied sciences Artificial intelligence Biological and medical sciences Brain–computer interface Computer science; control theory; systems Computer systems and distributed systems. User interface Data processing. List processing. Character string processing Electrodiagnosis. Electric activity recording Electroencephalograph Emotion classification Exact sciences and technology Feature reduction Investigative techniques, diagnostic techniques (general aspects) Manifold learning Medical sciences Memory organisation. Data processing Nervous system Software Support vector machine Electroencephalograph Support vector machine Manifold learning Emotion classification Feature reduction Brain–computer interface Brain Smoothing methods Electroencephalography Emotion emotionality Dynamical system Dynamic method Data reduction Electrodes Brain-computer interface Dimension reduction Experimental result Multidimensional analysis User interface Vector support machine Selection criterion Reduced order model Artificial intelligence Power spectrum
ISSN:	0925-2312, 1872-8286
Online Access:	Get full text
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