1.
Health Informatics J
; 24(2): 146-170, 2018 06.
Artigo
em Inglês
| MEDLINE
| ID: mdl-27644256
RESUMO
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.