Hapicare: A Healthcare Monitoring System with Self-Adaptive Coaching using Probabilistic Reasoning
Hossain Kordestani, Roghayeh Mojarad, Abdelghani Chibani, Aomar Osmani, Yacine Amirat, Kamel Barkaoui, Wagdy Zahran · 2019
Patients with chronic conditions require medical care at their home. To this end, a smart follow-up and monitoring system is proposed, called Hapicare; which applies ontology-based uncertain reasoning over IoT sensors data and self-assessment. While similar approaches rely on certain events and rules, the proposed monitoring system is based on probabilistic reasoning that interleaves Bayesian and non-monotonic inference. The latter is defined by using rule-based on concepts of the Semantic Sensor Network (SSN) and the SNOMED-CT ontologies. This system also considers uncertain contextual information captured from sensors and the history of patients in order to better diagnose the current situation and trigger suitable reactions. It allows also handling overlaps between symptoms, the possibility of errors and hidden facts. Hapicare is developed in the context of Medolution EU project.