The Relationship between Chaotic Characteristics of Physiological Signals and Emotion Based on Approximate Entropy

DOI

10.2991/iccsee.2013.141How to use a DOI?

Keywords

Respiratary signal, Electrocardiography signal, Emotion Recognition, Approximate entropy

Abstract

Emotion recognition is an important part in affective computing. It is the basis of building a harmonious man-machine environment. Respiratory (RSP) signal and electrocardiogram (ECG) signal are one of the main study objects in the emotion recognition based on physiological signal. The variations of the RSP signal and the ECG signal is one of the true performances of the human emotions. Through the analyses of the RSP signal and the ECG signal, we can recognize the inner emotion variations of human beings. This lays the foundation for the system modeling of emotion recognition. In this paper, we study the approximate entropy extraction of the physiological signals and analyze the chaotic characteristics and frequency domain characteristics of the approximate entropy under different emotions. The study results show that the different emotion status is corresponding to different approximate entropy and different variations in the frequency domain.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chun-yan Nie
AU  - Hai-xin Sun
AU  - Ju Wang
PY  - 2013/03
DA  - 2013/03
TI  - The Relationship between Chaotic Characteristics of Physiological Signals and Emotion Based on Approximate Entropy
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 552
EP  - 555
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.141
DO  - 10.2991/iccsee.2013.141
ID  - Nie2013/03
ER  -