基于实时脑电图的人类情感识别与可视化

Yisi Liu, O. Sourina, M. K. Nguyen
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引用次数: 284

摘要

情感伴随着每个人的日常生活,在非语言交际中扮演着关键的角色,对于理解人类行为至关重要。情感识别可以通过文本、语音、面部表情或手势来完成。在这篇论文中,我们集中于从脑电图(EEG)信号中识别“内心”情绪,因为人类可以控制他们的面部表情或语音语调。随着脑机接口应用的日益重要,以及以人为中心和人为驱动的数字媒体交互新形式的发展,从脑电信号中自动识别情绪的需求和重要性日益增加。提出了基于分形维数的基本情绪量化算法,并描述了其在三维虚拟环境中的反馈实现。用户的情绪被实时地识别和可视化在他/她的化身上,为人机界面增加了一个所谓的“情感维度”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-Time EEG-Based Human Emotion Recognition and Visualization
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 “inner” 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 “emotion dimension” to human computer interfaces.
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