Ontology-based personalized system to support patients at home

Abstract

Chronic diseases are incurable diseases that require long term supervision and treatments by medical professionals. The most common chronic diseases are cardiovascular disease, obesity, diabetes respiratory diseases and cancer. With information and communication technology many applications have been implemented to facilitate different clinical decision making process. With new technology, personalized healthcare systems are in place to enable patients with chronic diseases to acquire continuous and long-term medical services at home. This improves healthcare delivery since medical services can be accessed at any place. Today high prevalence of chronic diseases poses technological challenges to existing personalized healthcare systems including data integration and personalized recommendation plan. This research investigates how semantic technologies could be used to address the above challenges. The goal of this thesis is to use semantic technology for building ontology knowledge repository to provide data integration and medical recommendations for home based diabetes management systems. This ontology focuses on organizing knowledge related to vital sign measurement, questionnaire and recommendations for diabetic patients. To enter and link concepts and data for diabetes ontology, we used Protégé-owl. The ontology model provides knowledge into which information on individual patient including vital-sign data, questionnaires based information and recommendation are derived. Based on ontology’s structure, the model can collect, store and share information from heterogeneous sources, Reason over knowledge. Furthermore, ontology has been proven to be a better way of describing managed data. Therefore ontology based technology could be implemented in the personalized systems to enhance remote care for home-patient. Keywords: