Emotion Recognition from Physiological Sensor Data - Learning and Applications
Date Issued
2007
Date
2007
Author(s)
Chen, Yu-Hsin
DOI
en-US
Abstract
Emotion as a concept is usually forgotten in service providing and interactive communication. As content service and communication develop, emotion becomes more and more important in these research fields. In this research, I use bio-sensors to collect physiological signals from human subjects in different emotion states. The signals include sensor data from blood volume pulse, skin conductance, skin temperature, and respiration. I extract the features from these signals, and then use support vector machine to learn a classifier. The recognition rate of emotion is about 97%.
Furthermore, a prototype application Cura is made. Cura is an ambient cube which shows emotion states depending on the recognition of emotion. It is a media to tell one's closer the emotion with privacy-concern. Cura is simple and nature so that human transmit the emotion directly. Furthermore, Cura also keeps the private of the emotion information. It leaves the decision to user themselves with who he/she shares the emotion.
Subjects
情緒辨識
生理訊號
emotion reconition
physiological signal
Type
thesis
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