Affiliations: [a]
Faculty of Engineering, School of Computer Science, Universidad Pedagógica y Tecnológica de Colombia, Avenida Central del Norte 39 – 115, Colombia
| [b] Universidad Santo Tomás, Colombia, Faculty of Electronics Engineering, Calle 19 N° 11 – 64, Colombia
Correspondence:
[*]
Corresponding author. Mauro Callejas-Cuervo, Faculty of Engineering, Computer Science Program, Universidad Pedagógica y Tecnológica de Colombia, Avenida Central del Norte 39 – 115, Colombia. E-mail: [email protected].
Abstract: This paper presents a system that allows for the identification of two values: arousal and valence, which represent the degree of stimulation in a subject, using Russell’s model of affect as a reference. To identify emotions, a step-by-step structure is used, which, based on statistical data from physiological signal metrics, generates the representative arousal value (direct correlation); from the PANAS questionnaire, the system generates the valence value (inverse correlation), as a first approximation to the techniques of emotion recognition without the use of artificial intelligence. The system gathers information concerning arousal activity from a subject using the following metrics: beats per minute (BPM), heart rate variability (HRV), the number of galvanic skin response (GSR) peaks in the skin conductance response (SCR) and forearm contraction time, using three physiological signals (Electrocardiogram - ECG, Galvanic Skin Response - GSR, Electromyography - EMG).
Keywords: Emotion recognition, personality traits, Russell’s model of affect, eysenck
personality theory, physiological signals
