Intelligent Monitoring of the Elderly in Home Environment

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.