Greenolive: An open platform for wellness management ecosystem

Proceedings of 2010 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2010

Volumn , Issue , 2010, Pages 88-93

  Zeng, Liangzhao ^a   Hsueh, Pei Yun ^a   Chang, Henry ^a   Chung, Christina ^b   Huang, Rick ^b  

^a IBM T J WATSON RESEARCH CENTER   (United States)

^b IBM CHINA RESEARCH LAB   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CHRONIC DISEASE; HEALTH CARE COSTS; HEALTHCARE QUALITY; INDEPENDENT SOFTWARE VENDORS; KEY COMPONENT; OTHER APPLICATIONS; SCALABILITY ISSUE; SOCIAL NETWORKS; STAND-ALONE SOFTWARE; VALUE ADDED APPLICATIONS; WELLNESS APPLICATIONS; WELLNESS MANAGEMENT; WELLNESS MONITORING;

DISEASES; ECOSYSTEMS; INFORMATION SCIENCE;

ENTERPRISE RESOURCE MANAGEMENT;

EID: 77957808364     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SOLI.2010.5551612     Document Type: Conference Paper

References (19)

1. Continua Health Alliance, http://www.continuaalliance.org/.
2. Facebook, http://www.facebook.coml.
3. Force.com, http://www.force.com/.
4. Type 2 Diabetes Mellitus, Edited by Mark N. Feinglos, M. Angelyn Bethel, Humanna Press.
5. PMML, http://www.dmg.org/.
6. M. Koch, F. F.-F. Schmid, V. Zoete, and M. Meuwly. Insulin: A model system for nanomedicine? Nanomedicine (Lond), 1(3):373-378, Oct 2006.
7. T. Bremer and D. A. Gough. Is blood glucose predictable from previous values? A solicitation for data. Diabetes, 48(3), Mar 1999.
8. L. Magni, D. M. Raimondo, L. Bossi, C. D. Man, G. D. Nicolao, B. Kovatchev, and C. Cobelli. Model predictive control of type 1 diabetes: an in silico trial. J Diabetes Sci Technol, 1(6):804-812, Nov 2007.
9. The Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group. Continuous glucose monitoring and intensive treatment of type 1 diabetes. New England Journal of Medicine, 359(14):1464-1476, 2008.
10. R. S. Parker, F. J. D. III, J. H. Ward, and N. A. Peppas. Robust h glucose control in diabetes using a physiological model. Bioengineering, food, and natural products, 46(12), 2000.
11. W. Sandham, E. Lehmann, D. Hamilton, M. Sandilands, and G. Scotsig. Simulating and predicting blood glucose levels for improved diabetes healthcare. In 4th IET International Conference on Advances in Medical, Signal and Information Processing, 2008.
12. P. Dua, F. J. Doyle, and E. N. Pistikopoulos. Model-based blood glucose control for type 1 diabetes via parametric prograrmning. IEEE Trans. Biomed. Eng, 53(8):1478-1491, 2006.
13. A. Gani, A. V. Gribok, Y. Lu, W. K. Ward, R. A. Vigersky, and J. Reifman. Universal glucose models for predicting subcutaneous glucose concentration in humans. IEEE Transactions on Information Technology in Biomedicine, 14(1), 2010.
14. C. Bailey. The diabetes prevention program: headline results. Br J Diabetes Vasc Dis, 1 :62-64, 2001.
15. T. Saaristo, M. Peltonen, S. Keinanen-Kiukaanniemi, M. Vanhala, J. Saltevo, 1. Niskanen, H. Oksa, E. Korpi-Hyovalti, J. Tuomilehto, and F.-D. S. Group. National type 2 diabetes prevention prograrmne in finland: Fin-d2d. Int J Circumpolar Health, 66(2), Apr 2007.
16. W. Kroeze, A. Werkman, and J. Brug. A systematic review of randomized trials on the effectiveness of computer-tailored education on physical activity and dietary behaviors. Annals of Behavioral Medicine, pages 205-223, 2008.
17. A. Kinmonth, A. Woodcock, S. Griffin, N. Spiegal, M. Campbell, and the Team. Randomised controlled trial of patient centred care of diabetes in general practice: impact on current wellbeing and future disease risk. BMJ, 317:1202-1208, 1998.
18. X. Pan, G. Li, Y. Hu, J. Wang, W. Yang, and Z. An. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance: The Da-Qing diabetes study. Diabetes Care, 20, 1997.
19. A. D. Gaetano, T. Hardy, B. Beck, E. Abu-Raddad, P. Palumbo, J. Bue-Valleskey, and N. Perksen. Mathematical models of diabetes progression. Am J Physiol Endocrinol Metab, 295:1462-1479, 2008.