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Kinematic and dynamic models are used to create simplified, yet accurate representations of reality. In application to biological systems, there is often a choice on what level of complexity is appropriate for the model. This paper introduces a structured method for obtaining an accurate model that can represent the sit-to-stand motion and reproduce the associated contact forces in the standing phase...
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 for collecting driver data that allows us to...
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 the hybrid system, is posed as an infinite...
Human behavioral interventions aimed at improving health can benefit from objective wearable sensor data and mathematical models. Smartphone-based sensing is particularly practical for monitoring behavioral patterns because smartphones are fairly common, are carried by individuals throughout their daily lives, offer a variety of sensing modalities, and can facilitate various forms of user feedback...
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 emergency maneuvers. In order to improve...
While ℓ1-minimization (ℓ1-min) has recently been studied extensively in optimization, the high computational cost associated with the traditional algorithms has largely hindered their application to high-dimensional, large-scale problems. This paper discusses accelerated ℓ1-min techniques using augmented Lagrangian methods and its parallelization leveraging the parallelism available in modern GPU...
Within context-aware computing, there is a growing interest in linking localization technologies with activity recognition in a cooperative way. Existing research works in this field face two main difficulties: lack of accuracy in their solutions and/or sophisticated hardware requirements. To avoid these issues, we present a light-weight, low-cost and high-accuracy system for localization and activity...
In this paper we propose the integration of computer vision with accelerometry in order to provide a precise localization solution. In terms of accelerometry, our approach makes use of a single off-the-shelf accelerometer on the waist to precisely obtain the velocity of the user. This allows us to calculate the kinetic energy of the person being tracked, and link the accelerometry data with the computer...
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 determine the velocity and stride length of the...
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