Abstract
In the paper problem of planning training protocol with taking into account limitations on the training intensity due to the health problems of the exerciser is considered. In the first part of the work short introduction to existing solutions in the area of eHealth applications is given. Next, architecture of the eHealth system to support exerciser training is discussed. The main functionalities of proposed system are pointed out and challenges are highlighted. The concept of context-awareness and personalization is stressed. At the end the problem of model based optimisation of the training protocol is formulated.
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References
Cheng, T.M., Savkin, A.V., Celler, B.G., Su, S.W., Wang, L.: Nonlinear Modeling and Control of Human Heart Rate Response During Exercise With Various Work Load Intensities. IEEE Trans. On Biomedical Engineering 55(11), 2499–2508 (2008)
Cheng, T.M., Savkin, A.V., Celler, B.G., Su, S.W., Wang, L.: Heart Rate Regulation During Exercise with Various Loads: Identification and Nonlinear H inf Control. In: Proc. of the 17th World Congress of The International Federation of Automatic Control, pp. 11618–11623. IFAC, Seoul (2008)
Dalla, M.C., et al.: GIM, Simulation Software of Meal Glucose-Insulin Model. Journal of Diabetes Science and Technology 1, 323–330 (2007)
Dalla, M.C., et al.: Meal Simulation Model of the Glucose-Insulin System. IEEE Transactions On Biomedical Engineering 54, 1740–1749 (2007)
Dalla, M.C., et al.: Physical Activity into the Meal Glucose-Insulin Model of Type 1 Diabetes: In Silico Studies. Journal of Diabetes Science and Technology 3, 56–67 (2009)
Grandinetti, L., Pisacane, O.: Web based prediction for diabetes treatment. Future Generation Computer Systems 27, 139–147 (2011)
Greene, B.R., McGrath, D., O’Neill, R., O’Donovan, K.J., Burns, A., Caulfield, B.: An adaptive gyroscope-based algorithm for temporal gait analysis. Journal of Medical And Biological Engineering And Computing 48, 1251–1260 (2010)
Johnson, D., Perkins, C., Arkko, J.: RFC: 3775. Mobility Support in IPv6. Technical report, Network Working Group (2004)
Lornicz, K., Chen, B., Challen, G.W.: Mercury: A Wearable Sensor Network Platform for High-Fidelity Motion Analysis (2009)
Mougiakakou, S.G., et al.: SMARTDIAB: A Communication and Information Technology Approach for the Intelligent Monitoring, Management and Follow-up of Type 1 Diabetes Patients. IEEE Transactions on Information Technology in Biomedicine 14, 622–633 (2010)
Twomey, N., Faul, S., Marnane, W.P.: Comparison of accelerometer-based energy expenditure estimation algorithms. In: 4th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), pp. 1–8. IEEE Press, Munich (2010)
BodyTel, http://www.bodytel.com
LifeScan, http://www.lifescan.com
MyGlucoHealth, http://www.myglucohealth.net
World Health Organization, http://www.who.int
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Brzostowski, K., Drapała, J., Świątek, J. (2012). System Analysis Techniques in eHealth Systems: A Case Study. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Intelligent Information and Database Systems. ACIIDS 2012. Lecture Notes in Computer Science(), vol 7196. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28487-8_8
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DOI: https://doi.org/10.1007/978-3-642-28487-8_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28486-1
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