Affective computing using clustering method for mapping human's emotion

Z. Zhang, Eiichiro Tanaka

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

3 Citations (Scopus)

Abstract

In this study, we proposed a method which could be used for mapping people's emotion state on the two-dimensional arousal-valence model of effect. The final target of our research is to apply this kind of emotional recognition system to robots or some assistant apparatus which service activities of daily living (ADL). Since in our previous studies, we have finished the work of recognizing people's emotion state on the dimension of arousal by evaluating subjects' heartbeat and LF/HF, which is calculated from the frequency domain analysis of HRV, as the second step's work, we focused on how to recognize people's emotion state on valence dimension. To be specific, we used some kinds of normative affective stimuluses to elicit subjects' emotional change, then collected multiple physiological data during this emotional stimulation process. Finally, as for data analyzing, we didn't use the supervised learning method, like SVM, but made a new attempt to apply the unsupervised clustering method to sample data, dividing the data set into several natural clusters by analyzing the physiological features we abstracted. The calculated results of our experiment have verified the feasibility of mapping human's emotion state on the two-dimensional arousal-valence model of effect at a quadrant level.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages235-240
Number of pages6
ISBN (Electronic)9781509059980
DOIs
Publication statusPublished - 2017 Aug 21
Event2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017 - Munich, Germany
Duration: 2017 Jul 32017 Jul 7

Other

Other2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017
CountryGermany
CityMunich
Period17/7/317/7/7

Fingerprint

Frequency domain analysis
Supervised learning
Robots
Experiments

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Science Applications
  • Software

Cite this

Zhang, Z., & Tanaka, E. (2017). Affective computing using clustering method for mapping human's emotion. In 2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017 (pp. 235-240). [8014023] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AIM.2017.8014023

Affective computing using clustering method for mapping human's emotion. / Zhang, Z.; Tanaka, Eiichiro.

2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 235-240 8014023.

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

Zhang, Z & Tanaka, E 2017, Affective computing using clustering method for mapping human's emotion. in 2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017., 8014023, Institute of Electrical and Electronics Engineers Inc., pp. 235-240, 2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017, Munich, Germany, 17/7/3. https://doi.org/10.1109/AIM.2017.8014023
Zhang Z, Tanaka E. Affective computing using clustering method for mapping human's emotion. In 2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 235-240. 8014023 https://doi.org/10.1109/AIM.2017.8014023
Zhang, Z. ; Tanaka, Eiichiro. / Affective computing using clustering method for mapping human's emotion. 2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 235-240
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