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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Vydáno v:	Neurocomputing (Amsterdam) Ročník 129; s. 94 - 106
Hlavní autoři:	Wang, Xiao-Wei, Nie, Dan, Lu, Bao-Liang
Médium:	Journal Article Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 10.04.2014 Elsevier
Témata:	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
On-line přístup:	Získat plný text
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