Emotion recognition system using short-term monitoring of physiological signals |
| |
Authors: | Email author" target="_blank">K?H?KimEmail author S?W?Bang S?R?Kim |
| |
Institution: | (1) Department of Biomedical Engineering, College of Health Science, Yonsei University, South Korea;(2) Human-computer Interaction Laboratory, Samsung Advanced Institute of Technology, South Korea |
| |
Abstract: | A physiological signal-based emotion recognition system is reported. The system was developed to operate as a user-independent
system, based on physiological signal databases obtained from multiple subjects. The input signals were electrocardiogram,
skin temperature variation and electrodermal activity, all of which were acquired without much discomfort from the body surface,
and can reflect the influence of emotion on the autonomic nervous system. The system consisted of preprocessing, feature extraction
and pattern classification stages. Preprocessing and feature extraction methods were devised so that emotion-specific characteristics
could be extracted from short-segment signals. Although the features were carefully extracted, their distribution formed a
classification problem, with large overlap among clusters and large variance within clusters. A support vector machine was
adopted as a pattern classifier to resolve this difficulty. Correct-classification ratios for 50 subjects were 78.4% and 61.8%,
for the recognition of three and four categories, respectively. |
| |
Keywords: | Emotion recognition Autonomic nervous system Physiological signal processing Support vector machine |
本文献已被 PubMed SpringerLink 等数据库收录! |
|