Emotion Recognition from Physiological Sensor Data - Learning and Applications
碩士 === 國立臺灣大學 === 資訊工程學研究所 === 95 === 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 physiolog...
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ndltd-TW-095NTU053920862015-12-07T04:04:11Z http://ndltd.ncl.edu.tw/handle/75908755447936367923 Emotion Recognition from Physiological Sensor Data - Learning and Applications 基於生理訊號之情緒辨識及應用 Yu-Hsin Chen 陳郁欣 碩士 國立臺灣大學 資訊工程學研究所 95 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. Jan Yung-jen Hsu 許永真 2007 學位論文 ; thesis 74 en_US |
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碩士 === 國立臺灣大學 === 資訊工程學研究所 === 95 === 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.
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Jan Yung-jen Hsu |
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Jan Yung-jen Hsu Yu-Hsin Chen 陳郁欣 |
author |
Yu-Hsin Chen 陳郁欣 |
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Yu-Hsin Chen 陳郁欣 Emotion Recognition from Physiological Sensor Data - Learning and Applications |
author_sort |
Yu-Hsin Chen |
title |
Emotion Recognition from Physiological Sensor Data - Learning and Applications |
title_short |
Emotion Recognition from Physiological Sensor Data - Learning and Applications |
title_full |
Emotion Recognition from Physiological Sensor Data - Learning and Applications |
title_fullStr |
Emotion Recognition from Physiological Sensor Data - Learning and Applications |
title_full_unstemmed |
Emotion Recognition from Physiological Sensor Data - Learning and Applications |
title_sort |
emotion recognition from physiological sensor data - learning and applications |
publishDate |
2007 |
url |
http://ndltd.ncl.edu.tw/handle/75908755447936367923 |
work_keys_str_mv |
AT yuhsinchen emotionrecognitionfromphysiologicalsensordatalearningandapplications AT chényùxīn emotionrecognitionfromphysiologicalsensordatalearningandapplications AT yuhsinchen jīyúshēnglǐxùnhàozhīqíngxùbiànshíjíyīngyòng AT chényùxīn jīyúshēnglǐxùnhàozhīqíngxùbiànshíjíyīngyòng |
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1718146414839595008 |