Estimation of User’s Affective Response on MusicContents Using Real-Time Analysis System of Physiological Signals

• Main Authors: Hsuan-Kai Wang, 王炫凱
• Other Authors: 陳志宏
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/55396891897711185457

碩士 === 國立臺灣大學 === 電機工程學研究所 === 97 === Integration of emotion recognition and portable devices such as cell phone could provide more completed information for people communication and better human-computer interaction. A real-time emotion recognition system for individuals could be implemented with related bio-information. In this research, specific music is chosen to elicit the user’s emotions (relaxed, positive and negative). The physiological signals were acquired through four biosensors: electromyogram, skin conductance, respiration and pulse. Physiological features are acquired by features extraction methods such as filtering, segmentation, calibration and normalization. At the same time, physiological features are classified using pattern recognition techniques. The accuracy of off-line analysis achieved 95.61% and 91.69% on recognition of “relaxed vs. excited” and “positive vs. negative”, respectively. Besides, our results show the tendency of user’s skin conductance responses matches other research results. Furthermore, the accuracy of real-time analysis are 94.69% and 81.00% on recognition of “relaxed vs. excited” and “positive vs. negative”, respectively. Finally, the limitations of real-time emotion recognition for individual are listed and will be solved in the future; there are still some works need to be optimized for implementation of a real-time emotion recognition system for individual.