Emotion monitoring sensor network using a drive recorder

Jinshan Luo, Haruka Yoshimoto, Yuki Okaniwa, Y. Hiramatsu, Atsushi Ito, Madoka Hasegawa
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Abstract

With the development of a mobility society, supporting drivers from the mental aspect for safe driving is an increasingly important issue before self-driving cars are dominant. We have developed a sensor network that uses biosignal sensors such as EEG, ECG, heart rate, and drivers’ operation of pedals and steering to measure drivers’ emotions. However, even though EEG may be an excellent index to estimate emotion, it is not practical to wear an EEG sensor while driving. So, we would like to add other methods that are easy to use and can support estimating drivers’ emotions. In this paper, we report the result of using the facial expression analysis technique to estimate a car driver’s stress and fatigue. The result shows that facial expression reflects driver emotion in most cases and is closely related to automotive operating status.
情感监测采用传感器网络驱动记录仪
随着移动社会的发展,在自动驾驶汽车占据主导地位之前,从心理层面支持驾驶员安全驾驶是一个越来越重要的问题。我们开发了一个传感器网络,利用脑电图、心电图、心率等生物信号传感器和驾驶员的踏板和转向操作来测量驾驶员的情绪。然而,尽管脑电图可能是一个很好的评估情绪的指标,但在驾驶时佩戴脑电图传感器是不切实际的。因此,我们希望添加其他易于使用且可以支持估计驾驶员情绪的方法。在本文中,我们报告了使用面部表情分析技术来估计汽车驾驶员的压力和疲劳的结果。结果表明,面部表情在大多数情况下反映了驾驶员的情绪,并且与汽车的运行状态密切相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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