Emotion monitoring sensor network using a drive recorder

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.