Abstract
Vital data measurement solely represents a snapshot of the patient’s condition. In case of deviant results health professionals can put them in relation to the daily constitution as well as the measurement circumstances and therefore interpret them accurately. Personal health telemonitoring actually provides no possibility for health professionals who interpret the recorded vital data to put them in relation with the context of the measurement and a patient’s daily activities. To tackle this contextual knowledge gap, we propose a personal health monitoring approach, which allows enriching measured vital data with contextual information from an Ambient Assisted Living (AAL) system. Therefore, it is possible to provide additional information, like the person’s activity before or during the vital data measurement. Patients and caregivers, which process monitored health data, gain advantages and can improve care giving process. To demonstrate the benefits we use the two use cases (1) cardiac rehabilitation and (2) mobile nursing care.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
HL7 v 2.6 ORU^R01 standard message.
References
Fitbit ultra, Fitbit Inc.: Available from http://www.fitbit.com/de/product (2012). Cited Sept 2012
Demiris, G.: Electronic home healthcare: concepts and challenges. Int. J. Electron. Healthc. 1, 4–16 (2004)
Alschuler, L., Beebe, C., Boone, K.W.: Implementation Guide for CDA Release 2.0 Personal Healthcare Monitoring Report (PHMR), Draft Standard for Trial Use, Release 1.1. (2010)
Continua Health Alliance. Continua Health Alliance: Available from http://www.continuaalliance.org (2012). Cited Sept 2012
IHE Int. Integrating the Healthcare Enterprise: Available from http://www.ihe.net (2012). Cited Sept 2012
Health Level Seven. Health level 7, Available from http://www.hl7.org (2012). Cited Sept 2012
Rantz, M., Aud, M., Alexander et al.: Tiger Place: An Innovative Educational and Research Environment, AAAI in Eldercare: New Solutions to Old Problems, Washington DC, USA (2008)
Becker, M.: Software architecture trends and promising technology for ambient assisted living systems, In Proceedings of Assisted Living Systems—Models, Architectures and Engineering Approaches, Dagstuhl, Germany, pp. 18 (2008)
Rantz, M.J., Marek, K.D., Aud, M. et al.: A technology and nursing collaboration to help older adults age in place. Nurs. Outlook 40–45 (2005)
Bamis, A., Lymberopoulos, D., Teixeira, T et al.: The behaviorscope framework for enabling ambient assisted living. Spec. Issue Int. J. Pers. Ubiquit. Comput. (2009)
Fogarty, J., Au, C., Hudson, S.E.: Sensing from the basement: a feasibility study of unobtrusive and low-cost home activity recognition. In Proceedings of the 19th annual ACM symposium on User interface software and technology (UIST ‘06), pp. 91–100, New York, USA, (2006)
Kurschl, W., Franz, B., Buchmayr, M., et al.: Situation-aware ambient assisted living and ambient intelligence data integration for efficient eldercare. In: Watfa, M.K. (ed.) E-Healthcare Systems and Wireless Communications: Current and Future Challenges (Contributions to Book: Part/Chapter/Section 15), IGI Global, pp. 315–348, (2011)
Buchmayr, M., Kurschl, W., Küng, J.: A simulator for generating and visualizing sensor data for ambient intelligence environments. In Proceedings of the 2nd International Conference on Ambient Systems, Networks and Technologies (ANT-2011), pp. 90–98 Niagara Falls, Canada, (2011)
Strasser, M., Helm, E., Schuler, A., Fuschlberger, M., Altendorfer, B.: Mobile access to healthcare monitoring data for patients and medical personnel. In: Proceedings of the XXIV Conference of the European Federation for Medical Informatics, Quality of Life through Quality of Information, MIE 2012, Pisa, Italy, 26–29 Aug 2012
Strasser, M., Helm, E., Franz, B., Mayr, H.: Mobile health solutions for empowered, health-conscious individuals and patients, In Proceedings of the 10th International Conference on Information Communication Technologies in Health, ICICTH 2012, Samos, Greece, 12–14 July 2012
Sourceforge. Hapi: the open source HL7 API for Java, 2012 [cited 2012 Jan]. Available from: http://hl7api.sourceforge.net/index.html
Open Health Tools Inc. Improving the world’s health and well-being by unleashing health IT innovation. Available from http://openhealthtools.org (2012). Cited Jan 2012
Mirth Corperation. Mirth Connect. Available from http://www.mirthcorp.com/products/mirth-connect (2012). Cited Jan 2012
Kühne, T.: Matters of (Meta-)Modeling. J. Softw. Syst. Model. 5(4), 369–385 (2006) (Springer, Berlin)
Franz, B., Mayr, H.: Providing technical and semantic interoperability for integrated healthcare using an IHE-compliant system. In: Proceedings of the IADIS International Conference e-Health 2011, Rome, Italy, 20–22 July 2011
Acknowledgments
This research is partially funded by the Austrian Research Promotion Agency (FFG), the European Regional Development Fund (ERDF) in cooperation with the Upper Austrian state government (REGIO 13, Innovative Upper Austria, Health Cluster). Any opinions, findings and conclusions or recommendations in this paper are those of the authors and do not necessarily represent the views of the research sponsors.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Franz, B., Buchmayr, M., Schuler, A., Kurschl, W. (2014). Context-Enriched Personal Health Monitoring. In: Wichert, R., Klausing, H. (eds) Ambient Assisted Living. Advanced Technologies and Societal Change. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37988-8_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-37988-8_6
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37987-1
Online ISBN: 978-3-642-37988-8
eBook Packages: EngineeringEngineering (R0)