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Patterns of Cardiovascular and Behavioral Movements in Life-Logging According to Social Emotions

  • Hana Lee
  • Youngho Jo
  • Heajin Kim
  • Mincheol Whang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 474)

Abstract

The purpose of this study was to determine the cardiovascular and behavioral patterns to develop a new algorithm of emotion recognition system through only behavioral patterns. However, to achieve this we must compare the features with both cardiovascular responses and subjective evaluations. Seven students were asked to wear PPG sensors and carry their smartphones to track locations and periodically evaluate subjective emotions. The social emotions were categorized into mutuality and sociality dimensions. As a result, in sociality, cardiovascular features implied significant patterns in 8 cardiovascular features (p < 0.01). In mutuality, significant patterns were implied only in total power (p < 0.01). Additionally, results for sociality in behavioral features implied significant patterns in transition time and total distance (p < 0.01). Cardiovascular and behavioral patterns are two factors that can determine the physiological effects of individuals according to emotions.

Keywords

Cardiovascular Behavior Social emotions Active Passive Optimistic Pessimistic 

Notes

Acknowledgments

This work was supported by the ICT R&D program of MSIP/IITP. [2015-0-00312, The development of technology for social life logging based on analyzing social emotion and intelligence of convergence contents].

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Hana Lee
    • 1
  • Youngho Jo
    • 2
  • Heajin Kim
    • 2
  • Mincheol Whang
    • 3
  1. 1.Department of Emotion EngineeringSangmyung UniversitySeoulRepublic of Korea
  2. 2.Team of Technology Development, Emotion Science CenterSeoulRepublic of Korea
  3. 3.Department of Intelligence Information EngineeringSangmyung UniversitySeoulRepublic of Korea

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