Semantic Enrichment of Vital Sign Streams through Ontology-based Context Modeling using Linked Data Approach

• The Internet of Things (IoT) creates an ecosystem that connects people and objects through the internet. IoTenabled healthcare has revolutionized healthcare delivery by moving toward a more pervasive, patientcentered, and preventive care model. In the ongoing COVID-19 pandemic, it has also shown a great potential for effective remote patient health monitoring and management, which leads to preventing straining the healthcare system. Nevertheless, due to the heterogeneity of data sources and technologies, IoT-enabled healthcare systems often operate in vertical silos, hampering interoperability across different systems. Consequently, such sensory data are rarely shared nor integrated, which can undermine the full potential of IoT-enabled healthcare. Applying semantic technologies to IoT is a promising approach for fulfilling heterogeneity, contextualization, and situation-awareness requirements for real-time healthcare solutions. However, the enrichment of sensor streams has been under-explored in the existing literature. There is also a need for an ontology that enables effective patient health monitoring and management during infectious disease outbreaks. This study, therefore, aims to extend the existing ontology to allow patient health monitoring for the prevention, early detection, and mitigation of patient deterioration. We evaluated the extended ontology using competency questions and illustrated a proof-of-concept of ontology-based semantic representation of vital sign streams.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Information Systems (hsv//eng)

Nyckelord

Internet of Things (IoT)

Semantic Enrichment

Ontology

Linked Data

Patient Health Monitoring

Patient Management

Vital Sign

Healthcare

Infectious Disease Outbreak

data- och systemvetenskap

Computer and Systems Sciences

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)