Home // eTELEMED 2020, The Twelfth International Conference on eHealth, Telemedicine, and Social Medicine // View article
Authors:
Antonios Pliatsios
Thanos Stavropoulos
Dimitris Strantsalis
Vasileios Kassiano
Spiros Nikolopoulos
Ioannis Kompatsiaris
Keywords: Ontology; Event Detection; Semantic Web; SPIN; Reasoning; Rule-Based Systems; Dementia
Abstract:
In this paper, we describe a rule-based framework for the detection of health-related problems of people with dementia. The framework combines a novel ontology for lifestyle data (steps, sleep duration and heart rate measurements) and health-related problem representation and a novel set of SPARQL Inferencing Notation (SPIN) Rules to infer problems from lifestyle data. Both the ontology and the rule set are designed based on clinical expert knowledge in the field of dementia. More specifically, lifestyle data is acquired from lifestyle wearable devices in the market, making the system affordable and convenient. A model based on Semantic Web technology, Web Ontology Language (OWL), is used to formally represent and integrate sensor measurements, which promotes interoperability with other models and data exchange. SPIN rules offer the benefit of simplicity and flexibility as opposed to other rule representations in the domain. A proof-of-concept scenario is realized, showing data gathered from a real subject and the generation of expected problems by the framework.
Pages: 172 to 177
Copyright: Copyright (c) IARIA, 2020
Publication date: March 22, 2020
Published in: conference
ISSN: 2308-4359
ISBN: 978-1-61208-763-4
Location: Valencia, Spain
Dates: from November 21, 2020 to November 25, 2020