A logic programming approach to home monitoring for risk prevention in assisted living

Monitoring a patient in his home environment is necessary to ensure continuity of care in home settings, but this activity must not be too much invasive and a burden for clinicians. For this reason we prototyped a system called SINDI (Secure and INDependent lIving), focused on i) collecting a limited amount of data about the person and the environment through Wireless Sensor Networks (WSN), and ii) reasoning about these data both to contextualize them and to support clinicians in understanding patients' well being as well as in predicting possible evolutions of their health. Our hierarchical logic-based model of health combines data from different sources, sensor data, tests results, commonsense knowledge and patient's clinical profile at the lower level, and correlation rules between aspects of health (items) across upper levels. The logical formalization and the reasoning process are based on Answer Set Programming. The expressive power of this logic programming paradigm allows efficient reasoning to support prevention, while declarativity simplifies rules specification by clinicians and allows automatic encoding of knowledge. This paper describes how these issues have been targeted in the application scenario of the SINDI system