Title
SAREF4health: IoT standard-based ontology-driven healthcare systems
Author
Moreira, J.
Ferreira Pires, L.
Sinderen, M.V.
Daniele, L.
Contributor
Hitzler, P. (editor)
Borgo, S. (editor)
Kutz, O. (editor)
Publication year
2018
Abstract
Recently, a number of ontology-driven healthcare systems have been leveraged by the Internet-of-Things (IoT) technologies, which offer opportunities to improve patient monitoring and abnormal situation detection with support of medical wearables and cloud infrastructure. Usually, these systems rely on IoT ontologies to represent sensor data observations. The ETSI Smart Appliances REFerence (SAREF) IoT ontology is an extensible industry-oriented standard. In this paper, we discuss the verbosity problem of SAREF when used for real-time electrocardiography (ECG), emphasizing the requirement of representing time series. We compared the main ontologies in this context according to quality, message size (payload), IoT-orientation and standardization. We also introduce a SAREF4health extension to tackle the verbosity problem. In the SAREF4health development we followed ontology-driven conceptual modelling, in which an ECG ontology grounded in the Unified Foundational Ontology (UFO) plays the role of a reference model. The methodology was enhanced by a standardization procedure and considers the RDF serialization of the HL7 Fast Healthcare Interoperability Resources (FHIR) standard. The validation of SAREF4health includes the use cases of an early warning system that uses ECG data to detect accidents with truck drivers in a port area. A prototype that integrates an existing ECG wearable with cloud infrastructure demonstrates the performance impact of SAREF4health considering IoT constraints. Our results show that SAREF4health is adequate to enable semantic interoperability of IoT solutions that need to deal with frequency-based time series. Design decisions regarding the trade-off between ontology quality and aggregation representation are also discussed. © 2018 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
Subject
Health ontology
Ontology-driven conceptual modelling
Ontology-driven healthcare system
SAREF. ECG monitoring
Economic and social effects
Electrocardiography
Health care
Information systems
Information use
Interoperability
Ontology
Patient monitoring
Semantic Web
Semantics
Standardization
Time series
Truck drivers
Wearable technology
Cloud infrastructures
Conceptual modelling
Ecg monitoring
Health-care system
Healthcare Interoperability
Internet of thing (IOT)
Semantic interoperability
Unified foundational ontologies (UFO)
To reference this document use:
http://resolver.tudelft.nl/uuid:55092ca3-ea88-4a9f-9654-202fe04850ab
DOI
https://doi.org/10.3233/978-1-61499-910-2-239
TNO identifier
842709
Publisher
IOS Press
ISSN
0922-6389
Source
Frontiers in Artificial Intelligence and Applications. 10th International Conference Formal Ontology in Information Systems, FOIS 2018. 17 September 2018 through 21 September 2018, 306 (306), 239-252
Document type
conference paper