Influence of EQ on the Difference of Biometric Emotion and Self-evaluated Emotion

Reiji Yoshida, Midori Sugaya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

There are many methods to estimating human emotions based on data obtained by sensors. The well-known examples are emotion recognition by analyzing image data of the facial expression and speech emotion recognition analyzing voice data. However, since facial expressions and speech can be arbitrarily changed, they can be said to lack objectivity, which is necessary for emotion estimation. Therefore, emotional analysis using biological signal such as heartbeat and brain waves has been studied. Biological signal cannot be changed arbitrarily, therefore can be said to suit the necessity of being objective, meaning more suitable for emotion estimation. To measure the accuracy of the emotion estimation method using biological signal, it is common to obtain the degree of error between the estimation method and subjective evaluation of one’s emotion. However, the problem with this method is that there is no guarantee that the subjective evaluation is equal to the actual “real feeling” that one’s embracing. Therefore, in this study, we evaluated the emotion estimation method using biological signal using Emotional Intelligence Quotient (EQ). We examined whether the degree of error between the emotion estimation by biological signal and subjective evaluation of one’s emotion can be explained by the level of EQ. In this study, emotions were estimated using biometric data calculated by brainwaves and heartbeat obtained from sensors. As a result, we were able to show the effectiveness of EQ as the indicator of how close bio-estimated emotion is to the subjective emotion evaluation.

Original languageEnglish
Title of host publicationHuman-Computer Interaction. Recognition and Interaction Technologies - Thematic Area, HCI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings
EditorsMasaaki Kurosu
PublisherSpringer Verlag
Pages191-200
Number of pages10
ISBN (Print)9783030226428
DOIs
Publication statusPublished - 2019 Jan 1
EventThematic Area on Human Computer Interaction, HCI 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019 - Orlando, United States
Duration: 2019 Jul 262019 Jul 31

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11567 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceThematic Area on Human Computer Interaction, HCI 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019
CountryUnited States
CityOrlando
Period19/7/2619/7/31

Keywords

  • Emotion estimation
  • Emotional intelligence quotient
  • Emotions in HCI

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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