Intelligent Monitoring of the Elderly in Home Environment
Boštjan Kaluža, Erik Dovgan, Violeta Mirchevska, Mitja Luštrek, Matjaž Gams · National Conference on Artificial Intelligence · 2011
Demographic predictions of population aged 65 and over suggest the need for telemedicine applications in the eldercare domain. Current solutions are mainly focused on fall detection. This paper presents a working prototype of a system that in addition to fall detection monitors a variety of user’s behavior characteristics that help raise awareness of health risks. It monitors the state of user’s health, and more importantly, detects changes in behavior characteristics that potentially indicate a forthcoming or current disease, illness or some other disability. The system utilizes domain knowledge from medical literature on quantitative behavior analysis and combines it with an outlier-detection algorithm in order to identify anomalous behavior. Preliminary results with the working prototype are promising, showing a potential to deploy the system in practice.