V2iFi: in-Vehicle Vital Sign Monitoring via Compact RF Sensing

Given the significant amount of time people spend in vehicles, health issues under driving condition have become a major concern. Such issues may vary from fatigue, asthma, stroke, to even heart attack, yet they can be adequately indicated by vital signs and abnormal activities. Therefore, in-vehicle vital sign monitoring can help us predict and hence prevent these issues. Whereas existing sensor-based (including camera) methods could be used to detect these indicators, privacy concern and system complexity both call for a convenient yet effective and robust alternative. This paper aims to develop V 2 iFi, an intelligent system performing monitoring tasks using a COTS impulse radio mounted on the windshield. V 2 iFi is capable of reliably detecting driver's vital signs under driving condition and with the presence of passengers, thus allowing for potentially inferring corresponding health issues. Compared with prior work based on Wi-Fi CSI, V 2 iFi is able to distinguish reflected signals from multiple users, and hence provide finer-grained measurements under more realistic settings. We evaluate V 2 iFi both in lab environments and during real-life road tests; the results demonstrate that respiratory rate, heart rate, and heart rate variability can all be estimated accurately. Based on these estimation results, we further discuss how machine learning models can be applied on top of V 2 iFi so as to improve both physiological and psychological wellbeing in driving environments. CCS Concepts: • Applied computing → Consumer health; • Hardware → Sensor applications and deployments; • Humancentered computing → Ubiquitous and mobile computing systems and tools.