Recognition of human emotions based on user context and brain signals applied to electrical power systems operators evaluation

Article type: Research Article

Authors: Rached, Taciana Saad | Vieira, Maria de Fátima Queiroz | Santos, Danilo | Perkusich, Angelo^{; *} | Almeida, Hyggo

Affiliations: Embedded and Pervasive Computing Laboratory, Electrical Engineering Department, Electrical Engineering and Informatics Center, Federal University of Campina Grande, Campina Grande, PB, Brazil

Correspondence: [*] Corresponding author. Angelo Perkusich, Embedded and Pervasive Computing Laboratory, Electrical Engineering Department, Electrical Engineering and Informatics Center, Federal University of Campina Grande, CP 10105, 58429-970, Campina Grande, PB, Brazil. E-mail: [email protected].

Abstract: In this article, we propose a method to recognize human emotions based on user context and brain signals. We evaluated the method through an experiment during which individuals performed tasks using a simulator for electrical power systems operator training. We collected user context through log data retrieval and brain signals using an Electroencephalography (EEG) portable monitor. The experimental results demonstrated that the method could be successfully applied to recognize the emotional states based on EEG signals and user context.

Keywords: Emotion recognition, electroencephalography, signal processing, context-awareness

DOI: 10.3233/JIFS-191923

Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 987-1003, 2020