Next Article in Journal / Special Issue
A Smart Kitchen for Ambient Assisted Living
Previous Article in Journal
Hyperpolarized NMR Probes for Biological Assays
Previous Article in Special Issue
Design of a Wireless Sensor Network Platform for Tele-Homecare
Sensors 2014, 14(1), 1598-1628; doi:10.3390/s140101598

Ontology-Driven Monitoring of Patient’s Vital Signs Enabling Personalized Medical Detection and Alert

1,* , 2
1 Internet Based Communication Networks and Services, Department of Information Technology—iMinds, Ghent University, Gaston Crommenlaan 8 Box 201, Ghent 9050, Belgium 2 Institute of Computer Science, Foundation for Research and Technology and the Department of Computer Science, University of Crete, Vassilika Vouton, P.O. Box 1385, Heraklion 71110, Greece 3 Department of Informatics Engineering, Technological Educational Institute of Crete, Estavromenos 71004, Greece 4 Computational Medicine Laboratory, FORTH-ICS, N.Plastira 100, Vassilika Vouton, Heraklion 71110, Greece
* Author to whom correspondence should be addressed.
Received: 2 December 2013 / Revised: 10 January 2014 / Accepted: 13 January 2014 / Published: 17 January 2014
View Full-Text   |   Download PDF [951 KB, uploaded 21 June 2014]   |   Browse Figures


A major challenge related to caring for patients with chronic conditions is the early detection of exacerbations of the disease. Medical personnel should be contacted immediately in order to intervene in time before an acute state is reached, ensuring patient safety. This paper proposes an approach to an ambient intelligence (AmI) framework supporting real-time remote monitoring of patients diagnosed with congestive heart failure (CHF). Its novelty is the integration of: (i) personalized monitoring of the patients health status and risk stage; (ii) intelligent alerting of the dedicated physician through the construction of medical workflows on-the-fly; and (iii) dynamic adaptation of the vital signs’ monitoring environment on any available device or smart phone located in close proximity to the physician depending on new medical measurements, additional disease specifications or the failure of the infrastructure. The intelligence lies in the adoption of semantics providing for a personalized and automated emergency alerting that smoothly interacts with the physician, regardless of his location, ensuring timely intervention during an emergency. It is evaluated on a medical emergency scenario, where in the case of exceeded patient thresholds, medical personnel are localized and contacted, presenting ad hoc information on the patient’s condition on the most suited device within the physician’s reach.
Keywords: medical workflows; ambient intelligence (AmI); congestive heart failure (CHF); semantic reasoning ; medical alarms; quality of service (QoS) medical workflows; ambient intelligence (AmI); congestive heart failure (CHF); semantic reasoning; medical alarms; quality of service (QoS)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
MDPI and ACS Style

Hristoskova, A.; Sakkalis, V.; Zacharioudakis, G.; Tsiknakis, M.; De Turck, F. Ontology-Driven Monitoring of Patient’s Vital Signs Enabling Personalized Medical Detection and Alert. Sensors 2014, 14, 1598-1628.

View more citation formats

Related Articles

Article Metrics

For more information on the journal, click here


Cited By

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert