Abstract
A major challenge related to caring for patients with chronic conditions is the early detection of exacerbations of the disease that may be of great significance. The dedicated clinical personnel should be contacted immediately and possibly intervene in time before an acute state is reached, by changing medication, or any other interventions, in order to ensure patient safety. This paper presents an Ambient Intelligence (AmI) framework supporting real-time remote monitoring of patients diagnosed with congestive heart failure. The remote monitoring environment, enhanced with semantic technologies, provides a personalized, accurate and fully automated emergency alerting system that smoothly interacts with the personal physician, regardless his/her physical location in order to ensure in time intervention in case of an emergency. The proposed framework is able to change context at runtime in case new medical services are registered, new rules are defined, or in case of network overload and failure situations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Gao, T., Greenspan, D., Welsh, M., Juang, R., Alm, A.: Vital signs monitoring and patient tracking over a wireless network. In: 27th Annual International Conference of the Engineering in Medicine and Biology Society, pp. 102–105 (2005)
Kostomanolakis, S., Kavlentakis, G., Sakkalis, V., Chronaki, C.E., Tsiknakis, M., Orphanoudakis, S.C.: Seamless Integration of Healthcare Processes related to Image Management and Communication in Primary Healthcare Centers. In: Proceedings of the 18th International Conference EuroPACS 2000, pp. 126–132 (2000)
White, L., Terner, C.: E-health, phase two: the imperative to integrate process automation with communication automation for large clinical reference laboratories. Journal of Healthcare Information Management (JHIM) 15(3), 295–305 (2001)
Chiou, Y.S., Wang, C.L., Yeh, S.C.: An adaptive location estimator using tracking algorithms for indoor WLANs. Wireless Networks 16(7), 1987–2012 (2010)
Kartakis, S., Tourlakis, P., Sakkalis, V., Zacharioudakis, G., Stephanidis, C.: Enhancing the patient experience through Ambient Intelligence applications in health care. In: 5th International Symposium on Ubiquitous Computing and Ambient Intelligence (UCAmI 2011), Riviera Maya, Mexico, December 6-8 (2011)
Kannel, W.B., D’Agostino, R.B., Silbershatz, H., Belanger, A.J., Wilson, P.W.F., Levy, D.: Profile for estimating risk of heart failure. Archives of Internal Medicine 159(11), 1197–1204 (1999)
Lloyd-Jones, D.M., Larson, M.G., Leip, E.P., Beiser, A., D’Agostino, R.B., Kannel, W.B., Murabito, J.M., Vasan, R.S., Benjamin, E.J., Levy, D.: Lifetime risk for developing congestive heart failure: the Framingham Heart Study. Circulation 106(24), 3068–3072 (2002)
OWL-S, Semantic Markup for Web Services, http://www.w3.org/Submission/OWL-S/
Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M.: SWRL: A Semantic Web Rule Language Combining OWL and RuleML (2004), http://www.w3.org/Submission/SWRL/
Pellet: OWL 2 Reasoner for Java, http://clarkparsia.com/pellet/
Vallée, M., Ramparany, F., Vercouter, L.: Dynamic service composition in ambient intelligence environments: a multi-agent approach. In: Proceeding of the First European Young Researcher Workshop on Service-Oriented Computing (2005)
Jovic, A., Gamberger, D., Krstacic, G.: Heart failure ontology. To appear in Bio-Algorithms and Med-Systems (2011)
Gamberger, D., Prcela, M., Jović, A., Šmuc, T., Parati, G., Valentini, M., Kawecka-Jaszcz, K., Styczkiewicz, K., Kononowicz, A., Candelieri, A., et al.: Medical knowledge representation within Heartfaid platform. In: Proc. of Biostec Int. Joint Conference on Biomedical Engineering Systems and Technologies, pp. 205–217 (2008)
Cândido, G., Barata, J., Colombo, A.W., Jammes, F.: Soa in reconfigurable supply chains: A research roadmap. Engineering Applications of Artificial Intelligence 22(6), 939–949 (2009)
Hristoskova, A., Moeyersoon, D., Van Hoecke, S., Verstichel, S., Decruyenaere, J., De Turck, F.: Dynamic composition of medical support services in the ICU: Platform and algorithm design details. Computer Methods and Programs in Biomedicine 100(3), 248–264 (2010)
Hristoskova, A., Volckaert, B., De Turck, F.: Framework Managing the Automated Construction and Runtime Adaptation of Service Mashups. In: International Workshop on Semantic Interoperability - IWSI (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Hristoskova, A., Sakkalis, V., Zacharioudakis, G., Tsiknakis, M., De Turck, F. (2012). Ontology-Driven Monitoring of Patient’s Vital Signs Enabling Personalized Medical Detection and Alert. In: Nikita, K.S., Lin, J.C., Fotiadis, D.I., Arredondo Waldmeyer, MT. (eds) Wireless Mobile Communication and Healthcare. MobiHealth 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 83. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29734-2_30
Download citation
DOI: https://doi.org/10.1007/978-3-642-29734-2_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29733-5
Online ISBN: 978-3-642-29734-2
eBook Packages: Computer ScienceComputer Science (R0)