TOWARDS KNOWLEDGE-BASED INTEGRATION OF PERSONAL HEALTH RECORD DATA FROM SENSORS AND PATIENT OBSERVATIONS
John Puentes, Jaakko Lähteenmäki
2011
Abstract
Personal Health Records (PHR) containing physiological data collected by multiple sensors are being increasingly used for wellness monitoring or disease management. These abundant complementary raw data could be nevertheless disregarded given the challenges to understand and process it. We propose a knowledge-based integration model of PHR data from sensors and personal observations, intended to facilitate decision support in scenarios of cardiovascular disease monitoring. The model relates knowledge at three data integration layers: elements identification, relations assessment, and refinement. Details on specific elements of each layer are provided, along with a discussion of use and implementation guidelines.
References
- Garg, M. K., Kim, D-J., Turaga, D. S., Prabhakaran, B., 2010. Multimodal analysis of body sensor network data streams for real-time healthcare. In Proc. ACM SIGMM International Conference on Multimedia Information Retrieval, Philadelphia, USA, pp. 469- 478.
- Halamka, J. D., Mandl, K. D., Tang, P. C., 2008. Early experiences with personal health records. Journal of the American Medical Informatics Association, vol. 15, no. 1, pp. 1-7.
- Han, J., Kamber, M., 2006. Data Mining: Concepts and Techniques. Morgan Kaufmann Series in Data Management Systems, 2nd edition, pp. 467-488.
- IEEE Health Informatics, 2009. Personal Health Device Communication, Part 11073-10441: Device Specialization - Cardiovascular Fitness and Activity Monitor. IEEE Engineering in Medicine and Biology Society, 11073™ Standard Committee, 85 pp.
- Jovanov, E., Poon, C., Yang, G-Z., Zhang, Y. T., 2009. Body sensor networks: from theory to emerging applications. Guest Editorial. IEEE Transactions on Information Technology in Biomedicine, vol. 13, no. 6, pp. 859-863.
- Kulkarni, P., Öztürk, Y., 2007. Requirements and design spaces of mobile medical care. ACM SIGMOBILE Mobile Computing and Communications Review, vol. 11, no. 3, pp. 12-30.
- Martínez-López, R., Millán-Ruiz, D., Martín-Domínguez, A., Toro-Escudero, M. A., 2008. An architecture for next-generation of telecare systems using ontologies, rules engines and data mining. In Proc. CIMCA, IAWTIC, and ISE International Conferences, Vienna, Austria, pp. 31-36.
- Stuntebeck, E. P., Davis II, J. S., Abowd, G. D., Blount, M., 2008. HealthSense: classification of health-related sensor data through user-assisted machine learning. In Proc. 9th workshop on Mobile Computing Systems and Applications, Napa Valley, USA, pp.1-5.
- Tang, P. C., Ash, J. S., Bates, D. W., Overhage, J. M., Sands, D. Z., 2006. Personal health records: definitions, benefits, and strategies for overcoming barriers to adoption. Journal of the American Medical Informatics Association, vol. 13, no. 2, pp. 121-126.
Paper Citation
in Harvard Style
Puentes J. and Lähteenmäki J. (2011). TOWARDS KNOWLEDGE-BASED INTEGRATION OF PERSONAL HEALTH RECORD DATA FROM SENSORS AND PATIENT OBSERVATIONS . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2011) ISBN 978-989-8425-34-8, pages 280-285. DOI: 10.5220/0003162502800285
in Bibtex Style
@conference{healthinf11,
author={John Puentes and Jaakko Lähteenmäki},
title={TOWARDS KNOWLEDGE-BASED INTEGRATION OF PERSONAL HEALTH RECORD DATA FROM SENSORS AND PATIENT OBSERVATIONS
},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2011)},
year={2011},
pages={280-285},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003162502800285},
isbn={978-989-8425-34-8},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2011)
TI - TOWARDS KNOWLEDGE-BASED INTEGRATION OF PERSONAL HEALTH RECORD DATA FROM SENSORS AND PATIENT OBSERVATIONS
SN - 978-989-8425-34-8
AU - Puentes J.
AU - Lähteenmäki J.
PY - 2011
SP - 280
EP - 285
DO - 10.5220/0003162502800285