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- Title
Emotional states recognition, implementing a low computational complexity strategy.
- Authors
Aguiñaga, Adrian Rodriguez; Ramirez, Miguel Angel Lopez
- Abstract
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.
- Subjects
ELECTROENCEPHALOGRAPHY; EMOTIONS; EXPERIMENTAL design; ARTIFICIAL neural networks
- Publication
Health Informatics Journal, 2018, Vol 24, Issue 2, p146
- ISSN
1460-4582
- Publication type
Article
- DOI
10.1177/1460458216661862