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Real-Time EEG-Based Human Emotion Recognition and Visualization

机译:基于实时脑电图的人类情感识别与可视化

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Emotions accompany everyone in the daily life, playing a key role in non-verbal communication, and they are essential to the understanding of human behavior. Emotion recognition could be done from the text, speech, facial expression or gesture. In this paper, we concentrate on recognition of ȁC;innerȁD; emotions from electroencephalogram (EEG) signals as humans could control their facial expressions or vocal intonation. The need and importance of the automatic emotion recognition from EEG signals has grown with increasing role of brain computer interface applications and development of new forms of human-centric and human-driven interaction with digital media. We propose fractal dimension based algorithm of quantification of basic emotions and describe its implementation as a feedback in 3D virtual environments. The user emotions are recognized and visualized in real time on his/her avatar adding one more so-called ȁC;emotion dimensionȁD; to human computer interfaces.
机译:情感伴随着每个人的日常生活,在非语言交流中起着关键作用,对于理解人类行为至关重要。可以从文本,语音,面部表情或手势中进行情感识别。在本文中,我们集中于对ȁC;内ȁD;脑电图(EEG)信号引起的情绪激动,因为人类可以控制其面部表情或声音语调。随着脑计算机接口应用程序的作用不断增强以及以人为中心和以人为驱动的新型数字媒体交互形式的发展,从脑电信号中自动情感识别的需求和重要性日益增长。我们提出了基于分形维数的基本情绪量化算法,并将其实现描述为3D虚拟环境中的反馈。用户的情绪在他/她的头像上实时识别并可视化,再添加一个所谓的ȁC;情感维度ȁD;到人机界面。

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