(Rev Med Chile 2015; 143: 14-21)

Ageing significantly increases the prevalence of chronic diseases. Public health services expenditures grow in a biased way because chronic diseases are responsible for 50% of healthcare costs. Telemonitoring and Home Support Systems (THSS) can act as early warning systems trying to forecast the worsening or exacerbation of chronic conditions. We propose a wireless sensor network for THSS of an adult living alone in his habitual residence. The system is evaluated by means of a discrete event simulation model using the activity scanning approach. Graphics from sensor data allow to present summarized reports to family and healthcare providers through web applications.

World population is ageing due to longer life expectancy worldwide. There is a trend in elderly people to live alone in their habitual residences in spite of health and safety risks. Smart Homes, intelligent environment systems deployed at elderly homes can act as early warning systems trying to forecast the worsening or exacerbation of the resident chronic conditions. Access to sensor datasets is essential for the development of an efficient real smart home. Procurement of such datasets is subject to several restrictions and difficulties. This paper describes the generation of synthetic datasets by means of a simulation model as a suitable alternative previous to the deployment of a real monitoring system. The collection of synthetic datasets will be used during the next project step to train and evaluate activity recognition methods and algorithms.

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