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基于生理信号的实时情感识别系统设计与实现

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基于生理信号的实时情感识别系统设计与实现
Design and Implementation of a Real-time Emotion Recognition System Based on Physiological signals
投稿时间：2018-10-20
DOI：10.15918/j.tbit1001-0645.2019.s1.032
中文关键词:生理信号情感识别特征提取分类识别
English Keywords:physiological signalsemotion recognitionfeature extractionclassification
基金项目:国家自然科学基金资助项目（61601028，61431007）；国家重点研发计划项目（2017YFB1002505）
作者单位E-mail
刘鑫北京理工大学 信息与电子学院, 北京 100081
钟曼莉北京理工大学 信息与电子学院, 北京 100081
林艳飞北京理工大学 信息与电子学院, 北京 100081linyf@bit.edu.cn
刘志文北京理工大学 信息与电子学院, 北京 100081
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中文摘要:
设计并实现基于生理信号的实时情感识别系统.以视频为刺激材料诱发受试者高兴、惊奇、悲伤、愤怒、恐惧、平静6种情感，通过MP160生理信号记录仪采集受试者相应情感下的心电、呼吸、脉搏波、皮肤温度、肌电、皮肤电导6种生理信号，采用PCA和SVM结合的算法实现情感的实时分类.最后，系统对4名在校学生进行了实验，6种情感的平均识别率为70%.
English Summary:
In this research, we designed and implemented a real-time emotion recognition system by using physiological signals. The video materials were used to stimulate subjects' emotions of happiness, surprise, sadness, anger, fear and calmness. The MP160 physiological recorder was used to collect the physiological signals of ECG, myoelectricity, skin conductance, respiration and skin temperature of the subjects under the each emotion condition. After preprocessing, the combined algorithm including PCA and SVM was used to realize real-time classification of emotions. Finally, the system took four students as the subjects of the experiments, and the average recognition rate of the six emotions was 70%.
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相关话题/信息 北京 北京理工大学 电子 生理

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