The Relationship between Chaotic Characteristics of Physiological Signals and Emotion Based on Approximate Entropy
- 10.2991/iccsee.2013.141How to use a DOI?
- Respiratary signal, Electrocardiography signal, Emotion Recognition, Approximate entropy
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.
- © 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/).
Cite this article
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 -