An EO/IR monitoring system for noncontact physiological signal analysis in automated vehicles

Personnel shortages in the military sector require deploying soldiers as effectively as possible. Increased vehicle automation, e.g. for displacements or for resupply convoys, can improve this effectiveness by lowering the mental load needed for driving. Drivers of automated vehicles resemble passengers and are thereby more susceptible to motion sickness than drivers of non-autonomous vehicles. It is useful to monitor potential motion sickness, to ensure personnel arrive fit for duty at their destination. Therefore, a system to automatically detect the presence of motion sickness would be beneficial. In this paper, we introduce a camera-based system that uses electro-optical (EO) and infrared (IR) video sets to monitor facial skin temperature and respiratory rate as a step towards camera-based motion sickness monitoring in autonomous vehicles. Our proof-of-concept system obtained sufficient measurement accuracy for use in an experimental setting in which participants were subjected to a condition that induced motion sickness. We discuss the successes and challenges encountered during system set-up and data analysis, and share insights relevant to the envisioned application in an autonomous vehicle. Specifically, we compare recordings with and without subject motion caused by the motion sickness inducing condition and discuss measurement inaccuracies that might be encountered because of IR thermal drift. Additionally, we reflect on obstacles that can arise when employing an EO/IR monitoring system in a military context.