SUMMARYThis paper presents the design, kinematics, dynamics and control of a low-cost parallel rehabilitation robot developed at the Universitat Politècnica de Valencia. Several position and force controllers have been tested to ensure accurate tracking performances. An orthopedic boot, equipped with a force sensor, has been placed over the platform of the parallel robot to perform exercises for injured ankles. Passive, active-assistive and active-resistive exercises have been implemented to train dorsi/plantar flexion, inversion and eversion ankle movements. In order to implement the controllers, the component-based middleware Orocos has been used with the advantage over other solutions that the whole scheme control can be implemented modularly. These modules are independent and can be configured and reconfigured in both configuration and runtime. This means that no specific knowledge is needed by medical staff, for example, to carry out rehabilitation exercises using this low-cost parallel robot. The integration between Orocos and ROS, with a CAD model displaying the actual position of the rehabilitation robot in real time, makes it possible to develop a teleoperation application. In addition, a teleoperated rehabilitation exercise can be performed by a specialist using a Wiimote (or any other Bluetooth device).
The Chikungunya virus is the cause of an emerging disease in Asia and Africa, and also in America, where the virus was first detected in 2006. In this paper, we present a mathematical model of the Chikungunya epidemic at the population level that incorporates the transmission vector. The epidemic threshold parameter R 0 for the extinction of disease is computed using the method of the next generation matrix, which allows for insights about what are the most relevant model parameters. Using Lyapunov function theory, some sufficient conditions for global stability of the the disease-free equilibrium are obtained. The proposed mathematical model of the Chikungunya epidemic is used to investigate and understand the importance of some specific model parameters and to give some explanation and understanding about the real infected cases with Chikungunya virus in Colombia for data belonging to the year 2015. In this study, we were able to estimate the value of the basic reproduction number R 0 . We use bootstrapping and Markov chain Monte Carlo techniques in order to study parameters’ identifiability. Finally, important policies and insights are provided that could help government health institutions in reducing the number of cases of Chikungunya in Colombia.
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