Two-dimensional emotion evaluation with multiple physiological signals

Jyun Rong Zhuang*, Ya Jing Guan, Hayato Nagayoshi, Louis Yuge, Hee Hyol Lee, Eiichiro Tanaka

*Corresponding author for this work

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

16 Citations (Scopus)


Extended roles of robots for activities of daily living (ADL) lead to researchers’ increasing attention to human-robot interaction. Emotional recognition has been regarded as an important issue from the human mental aspect. We are developing an assistive walking device which considers the correlation between physical assistance and mental conditions for the user. To connect the assistive device and user mental conditions, it is necessary to evaluate emotion in real-time. This study aims to develop a new method of two-dimensional valence-arousal model emotion evaluation with multiple physiological signals. We elicit users’ emotion change based on normative affective stimuli database, and further extract multiple physiological signals from the subjects. Moreover, we implement various algorithms (k-means, T method of MTS (Mahalanobis Taguchi System) and DNN (deep neural network)) for determining the emotional state from physiological data. Finally, the findings indicate that deep neural network method can precisely recognize the human emotional state.

Original languageEnglish
Title of host publicationAdvances in Affective and Pleasurable Design - Proceedings of the AHFE 2018 International Conference on Affective and Pleasurable Design, 2018
EditorsShuichi Fukuda
PublisherSpringer Verlag
Number of pages11
ISBN (Print)9783319949437
Publication statusPublished - 2019
EventAHFE International Conference on Affective and Pleasurable Design, 2018 - Orlando, United States
Duration: 2018 Jul 212018 Jul 25

Publication series

NameAdvances in Intelligent Systems and Computing
ISSN (Print)2194-5357


ConferenceAHFE International Conference on Affective and Pleasurable Design, 2018
Country/TerritoryUnited States


  • Emotion evaluation
  • Physiological data
  • Promotion of exercise
  • Rehabilitation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)


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