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    Item type:Publication,
    Medi-Kit: Developing a solution to improve attention on medical treatment
    (2017)
    Mondragón, Andrea
    ;
    Hoyos, Andrés de
    ;
    Trejo, Axayacatl
    ;
    González, Marco
    ;
    Ponce, Hiram  
    Leaving unattended a medical treatment may have consequences, from prolonging a recovery waiting time to mortal circumstances. rent technological solutions have been proposed for this problem, including pillboxes and automated pill dispensers. In that sense, this paper aims to present the development of an automatic pill dispenser to improve attention on medical treatment when a patient does not take medicine on time. The implementation considers two components: A fixed device that works as the main automated pill dispenser, and a portable device that can communicate with the fixed device in order to synchronize medical treatment information in both devices. Experimental results proves that this functional prototype improves the number of times a patient not forget to follow a medical treatment and it reduces the delays in taking pills. © 2017 IEEE.
    Scopus© Citations 9  12  2
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    A novel artificial organic control system for mobile robot navigation in assisted living using vision- and neural-based strategies
    (2018)
    Ponce, Hiram  
    ;
    Moya-Albor, Ernesto  
    ;
    Brieva, Jorge  
    Robots in assisted living (RAL) are an alternative to support families and professional caregivers with a wide range of possibilities to take care of elderly people. Navigation of mobile robots is a challenging problem due to the uncertainty and dynamics of environments found in the context of places for elderly. To accomplish this goal, the navigation system tries to replicate such a complicated process inspired on the perception and judgment of human beings. In this work, we propose a novel nature-inspired control system for mobile RAL navigation using an artificial organic controller enhanced with vision-based strategies such as Hermite optical flow (OF) and convolutional neural networks (CNNs). Particularly, the Hermite OF is employed for obstacle motion detection while CNNs are occupied for obstacle distance estimation. We train the CNN using OF visual features guided by ultrasonic sensor-based measures in a 3D scenario. Our application is oriented to avoid mobile and fixed obstacles using a monocular camera in a simulated environment. For the experiments, we use the robot simulator V-REP, which is an integrated development environment into a distributed control architecture. Security and smoothness metrics as well as quantitative evaluation are computed and analyzed. Results showed that the proposed method works successfully in simulation conditions.
    Scopus© Citations 7  14  1