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We present an open-source platform for wireless body sensor networks called DexterNet. The system supports real-time, persistent human monitoring in both indoor and outdoor environments. The platform utilizes a three-layer architecture to control heterogeneous body sensors. The first layer called the body sensor layer (BSL) deals with design of(More)
Threat assessment during semiautonomous driving is used to determine when correcting a driver's input is required. Since current semiautonomous systems perform threat assessment by predicting a vehicle's future state while treating the driver's input as a disturbance, autonomous controller intervention is limited to a restricted regime. Improving vehicle(More)
We address the problem of formally verifying quantitative properties of driver models. We first propose a novel stochastic model of the driver behavior based on Convex Markov Chains, i.e., Markov chains in which the transition probabilities are only known to lie in convex uncertainty sets. This formalism captures the intrinsic uncertainty in estimating(More)
During semi-autonomous driving, threat assessment is used to determine when controller intervention that overwrites or corrects the driver’s input is required. Since today’s semi-autonomous systems perform threat assessment by predicting the vehicle’s future state while treating the driver’s input as a disturbance, controller intervention is limited to just(More)
We present an application of an open source platform for wireless body sensor network called DexterNet to the problem of children's asthma. The architecture of the system consists of three layers. At the body sensor layer (BSL), the integrated monitoring of a child's activities, geographic location, and air pollution exposures occurs. At the personal(More)
Within biomedical engineering, the use of wearable wireless accelerometers for gait analysis can provide useful information for multiple health-related applications. The minimization of hardware for an accurate and simple estimation of the patient's velocity and stride length represents a difficult task. In this paper we propose a new methodology to(More)
In order to develop provably safe human-in-the-loop systems, accurate and precise models of human behavior must be developed. Driving is a good example of such a system because the driver has full control of the vehicle, and her likely actions are highly dependent on her mental state and the context of the current situation. This paper presents a testbed(More)
This paper presents an approach to computing the time-limited backwards reachable set (BRS) of a semialgebraic target set for controlled polynomial hybrid systems with semialgebraic state and input constraints. By relying on the notion of occupation measures, the computation of the BRS of a target set that may be distributed across distinct subsystems of(More)
This report describes a new experimental setup for human-in-the-loop simulations. A force feedback simulator with four axis motion has been setup for real-time driving experiments. The simulator will move to simulate the forces a driver feels while driving, which allows for a realistic experience for the driver. This setup allows for flexibility and control(More)
We present a mobile platform for body sensor networking based on a smartphone for lightweight signal processing of sensor mote data. The platform allows for local processing of data at both the sensor mote and smartphone levels, reducing the overhead of data transmission to remote services. We discuss how the smartphone platform not only provides the(More)