Reasoning Support for Risk Prediction and Prevention in Independent Living
A. Mileo, D. Merico, R. Bisiani

TL;DR
This paper presents SINDI, a sensor-based system using logic programming to support elderly care by inferring health status and predicting health evolutions with minimal invasive data collection.
Contribution
The novel hierarchical logic-based model integrates diverse data sources and employs Answer Set Programming for reasoning about health in elderly care.
Findings
Effective reasoning with incomplete data
Supports prediction of health changes
Simplifies knowledge encoding for caregivers
Abstract
In recent years there has been growing interest in solutions for the delivery of clinical care for the elderly, due to the large increase in aging population. Monitoring a patient in his home environment is necessary to ensure continuity of care in home settings, but, to be useful, this activity must not be too invasive for patients and a burden for caregivers. 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) inferring from these data enough information to support caregivers in understanding patients' well being and in predicting possible evolutions of their health. Our hierarchical logic-based model of health combines data from different sources, sensor data, tests results, common-sense knowledge and patient's clinical profile at the…
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Taxonomy
TopicsLogic, Reasoning, and Knowledge · Multi-Agent Systems and Negotiation · Semantic Web and Ontologies
