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研究生(外文):tai hung li
論文名稱(外文):Emotion Detection based on Human PulseSignal for Supporting Teachers to Conduct Interactive Learning with Students on Online Discussion Board
指導教授(外文):Chih-Ming Chen
外文關鍵詞:E-learningembedded systemscomputersystemFourier transformSVMphysiological signals
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In recent years, E-learning has been a popular learning mode due to the fast growth of the Internet and it has advantages in terms of high interaction, getting feedback immediately, and breaking the limitations of learning time and space. In addition, many studies indicated that the variations of learning emotions have key affection to the learning outcomes of E-learning and many studies also proposed that detecting human emotions by physiological signals is a practicable scheme.Accordingly, the study employed sensor, signal processing, communication and system on chip (SOC) techniques to develop a embedded human emotion detection system based on human pulse signals, which can detect three human emotions including nervous, peaceful, and joyous for supporting teachers to conduct interactive learning with students on online discussion board. There are totally ten volunteers who were invited to participate in this experiment. In the experiments, several selected web movies and computer games were applied to cause emotion responses.
Meanwhile, the pulse signals caused by emotion variations are retrieved by the developed embedded human emotion detection system and stored in the database for emotion analyses. To process the pulse signals for emotion detection, the extracted human pulse signals are first transformed by Fourier transform from time domain to frequency domain, then the transformed data is used to extract emotion features for training an emotion detection model by support vector machine (SVM). The accuracy rate of the modeling emotion detection mechanism evaluated by cross validation is 76.8254%. To further filter out noisy human pulse data, the accuracy rate of emotion detection evaluated by cross validation can be promoted from 76.824% to 79.7136%. Currently, the proposed human emotion detection mechanism has been successfully applied to the online discussion board to support teachers for conducting interactive
III learning with students.
第一章 緒論
第二章 文獻探討
第三章 系統架構與實驗過程
第四章 實驗結果分析
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