Abstract—The proposed paper is based on an integrated planning system for mandatory and regular assessment of the elderly’s state of being and, if necessary, their telemonitoring and assistance. Consequently, the scope and the purpose of this paper is to provide a new type of treatment (medicine), based on connectivity, collaboration, personalization and computing. The presented paper issues an adaptation of the Particle Swarm Optimization Algorithm to forecast the next episode of an elderly’s fall.
Index Terms—Elderly fall risk, elderly fall prediction, PSO.
Stan Ovidiu is with the Automation Department of Technical University of Cluj Napoca, Cluj, Romania (e-mail: Ovidiu.stan@aut.utcluj.ro).
Liviu Miclea is with the Automation Department of Technical University of Cluj Napoca, Cluj, Romania (e-mail: liviu.miclea@aut.utcluj.ro).
Anca Sarb is with the Design Engineering and Robotics Department, Faculty of Machine Building, Technical University of Cluj Napoca, Cluj, Romania (e-mail: anca.sarb@muri.utcluj.ro).
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Cite: Stan Ovidiu, Liviu Miclea, and Anca Sarb, "Elderly Fall Forecast Based on Adapted Particle Swarm Optimization Algorithm," International Journal of Modeling and Optimization vol. 7, no. 4, pp. 251-255, 2017.
