Emotional states recognition, implementing a low computational complexity strategy
2016 ◽
Vol 24
(2)
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pp. 146-170
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Keyword(s):
This article describes a methodology to recognize emotional states through an electroencephalography signals analysis, developed with the premise of reducing the computational burden that is associated with it, implementing a strategy that reduces the amount of data that must be processed by establishing a relationship between electrodes and Brodmann regions, so as to discard electrodes that do not provide relevant information to the identification process. Also some design suggestions to carry out a pattern recognition process by low computational complexity neural networks and support vector machines are presented, which obtain up to a 90.2% mean recognition rate.
2021 ◽
Keyword(s):
2016 ◽
Vol 15
(01)
◽
pp. 1650004
◽
2008 ◽
Vol 15
(2)
◽
pp. 203-218
2013 ◽
Vol 26
(3)
◽
pp. 81-98
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Keyword(s):
2003 ◽
Vol 16
(7-8)
◽
pp. 657-665
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