Ontology-Based Model to Support Ubiquitous Healthcare Systems for COPD Patients

Electronics. 2018;7(12):371 DOI 10.3390/electronics7120371

 

Journal Homepage

Journal Title: Electronics

ISSN: 2079-9292 (Online)

Publisher: MDPI AG

LCC Subject Category: Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics

Country of publisher: Switzerland

Language of fulltext: English

Full-text formats available: PDF, HTML, ePUB, XML

 

AUTHORS

Hicham Ajami (Department of Computer Sciences and Mathematics, University of Québec at Chicoutimi; Chicoutimi, QC G7H 2B1, Canada)
Hamid Mcheick (Department of Computer Sciences and Mathematics, University of Québec at Chicoutimi; Chicoutimi, QC G7H 2B1, Canada)

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 11 weeks

 

Abstract | Full Text

Over the past 30 years, information technology has gradually transformed the way health care is provisioned for patients. Chronic Obstructive Pulmonary Disease (COPD) is an incurable malady that threatens the lives of millions around the world. The huge amount of medical information in terms of complex interdependence between progression of health problems and various other factors makes the representation of data more challenging. This study investigated how formal semantic standards could be used for building an ontology knowledge repository to provide ubiquitous healthcare and medical recommendations for COPD patient to reduce preventable harm. The novel contribution of the suggested framework resides in the patient-centered monitoring approach, as we work to create dynamic adaptive protection services according to the current context of patient. This work executes a sequential modular approach consisting of patient, disease, location, devices, activities, environment and services to deliver personalized real-time medical care for COPD patients. The main benefits of this project are: (1) adhering to dynamic safe boundaries for the vital signs, which may vary depending on multiple factors; (2) assessing environmental risk factors; and (3) evaluating the patient’s daily activities through scheduled events to avoid potentially dangerous situations. This solution implements an interrelated set of ontologies with a logical base of Semantic Web Rule Language (SWRL) rules derived from the medical guidelines and expert pneumologists to handle all contextual situations.