Minería de texto para el estudio de un estado del arte en el uso de señales fisiológicas para la detección de emociones: una perspectiva en la interacción humano robot

Armando Alejandro Ruiz-Figueroa; Pavel Makagonov; Víctor Alberto  Gómez-Pérez; José Alberto  Cruz-Tolentino; Alejandro Jarillo-Silva

doi:10.29057/icbi.v10iEspecial5.10138

Armando Alejandro Ruiz-Figueroa Universidad de la Sierra Sur https://orcid.org/0000-0001-8789-3224
Pavel Makagonov Russian Presidential Academy of National Economy and Public Administration
Víctor Alberto Gómez-Pérez Universidad de la Sierra Sur https://orcid.org/0000-0002-7758-6690
José Alberto Cruz-Tolentino Universidad de la Sierra Sur https://orcid.org/0000-0002-5195-0597
Alejandro Jarillo-Silva Universidad de la Sierra Sur

DOI: https://doi.org/10.29057/icbi.v10iEspecial5.10138

Keywords: Biometrics, cluster analysis, cubic polynomial, emotion analysis

Abstract

This article presents an approach based on the analysis of abstracts to know the trend of the use of physiological signals, as well as the feasibility of applying these techniques in the induction of emotions and cognitive states in healthy people. The objective of this article is to determine the feasibility of developing technological tools that help detect the emotional and cognitive state of a user when interacting with a robot. For this, initially 8,623 abstracts were collected from the IEEE digital library, which are related
to the topics of neurometrics and biometrics during a period of approximately 50 years ago. However, when analyzing the results, it is concluded that they are of little use for the objective of this research, so the term “emotions” is added in the new search. The article number is reduced to 110, the life cycle model or S curve is reconstructed using the segment of the cubic polynomial. The results show that there is a feasibility and feasibility of considering biometrics and neurometrics in the detection of emotions.

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