TY - GEN
T1 - Influence of EQ on the Difference of Biometric Emotion and Self-evaluated Emotion
AU - Yoshida, Reiji
AU - Sugaya, Midori
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Emotion estimation
KW - Emotional intelligence quotient
KW - Emotions in HCI
UR - http://www.scopus.com/inward/record.url?scp=85069655698&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85069655698&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-22643-5_15
DO - 10.1007/978-3-030-22643-5_15
M3 - Conference contribution
AN - SCOPUS:85069655698
SN - 9783030226428
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 191
EP - 200
BT - Human-Computer Interaction. Recognition and Interaction Technologies - Thematic Area, HCI 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings
A2 - Kurosu, Masaaki
PB - Springer Verlag
T2 - Thematic Area on Human Computer Interaction, HCI 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019
Y2 - 26 July 2019 through 31 July 2019
ER -