Journal of Medical Systems

, Volume 35, Issue 5, pp 1245–1254 | Cite as

Body Area Networks for Ubiquitous Healthcare Applications: Opportunities and Challenges

  • Emil JovanovEmail author
  • Aleksandar Milenkovic


Body Area Networks integrated into mHealth systems are becoming a mature technology with unprecedented opportunities for personalized health monitoring and management. Potential applications include early detection of abnormal conditions, supervised rehabilitation, and wellness management. Such integrated mHealth systems can provide patients with increased confidence and a better quality of life, and promote healthy behavior and health awareness. Automatic integration of collected information and user’s inputs into research databases can provide medical community with opportunity to search for personalized trends and group patterns, allowing insights into disease evolution, the rehabilitation process, and the effects of drug therapy. A new generation of personalized monitoring systems will allow users to customize their systems and user interfaces and to interact with their social networks. With emergence of first commercial body area network systems, a number of system design issues are still to be resolved, such as seamless integration of information and ad-hoc interaction with ambient sensors and other networks, to enable their wider acceptance. In this paper we present state of technology, discuss promising new trends, opportunities and challenges of body area networks for ubiquitous health monitoring applications.


Wireless body area networks Body sensor networks Ubiquitous monitoring 



Body Area Network


Wireless Body Area Network


Body Sensor Network


Mobile Health System


Application Specific Integrated Circuit


Personal Area Network


Wide Area Network


  1. 1.
    Jovanov, E., Price, J., Raskovic, D., Kavi, K., Martin, T., and Adhami, R., “Wireless Personal Area Networks in Telemedical Environment”, Third IEEE EMBS Information Technology Applications in Biomedicine—Workshop of the International Telemedical Information Society ITAB ITIS 2000, Arlington, Virginia:22–27, November 2000.Google Scholar
  2. 2.
    Heile, B., Gifford, I., and Siep, T., “The IEEE P802.15 working group for wireless personal area networks.” IEEE Netw. 13(4):4–5, Jul. 1999.Google Scholar
  3. 3.
    Raskovic, D., Martin, T., and Jovanov, E., “Medical Monitoring Applications for Wearable Computing.” Comput. J. 47(4):495–504, July 2004.CrossRefGoogle Scholar
  4. 4.
    Istepanian, R. S. H., Jovanov, E., and Zhang, Y. T., “Guest Editorial Introduction to the Special Section on M-Health: Beyond Seamless Mobility and Global Wireless Health-Care Connectivity.” IEEE Trans. Inf. Technol. Biomed. 8(4):405–414, Dec. 2004.CrossRefGoogle Scholar
  5. 5.
    Jovanov, E., Milenkovic, A., Otto, C., and de Groen, P., “A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation.” J NeuroEng Rehabilitation. 2:6, 2005, March 1, 2005.CrossRefGoogle Scholar
  6. 6.
    Yang, G-Z., Body Sensor Networks, Ed. Springer, 2006.Google Scholar
  7. 7.
    Jovanov, E., Poon, C. Y., Yang, G. Z., and Zhang, Y. T., “Guest Editorial Body Sensor Networks: From Theory to Emerging Applications.” IEEE Trans. Inf. Technol. Biomed. 13(6):859–864, November 2009.CrossRefGoogle Scholar
  8. 8.
    Bonato, P.,“Wearable Sensors and Systems.” IEEE Eng. Med. Biol. Mag. 29(3):25–36, May–June 2010.CrossRefMathSciNetGoogle Scholar
  9. 9.
    Blueooth Alliance, (Dec 2010)
  10. 10.
    Zigbee Alliance, (Dec 2010)
  11. 11.
    Ant, (Dec 2010)
  12. 12.
    TI+Chipcon Low Power RF Guide, (Dec 2010)
  13. 13.
    Nordic Semiconductors, (Dec 2010).
  14. 14.
    Kalil, T., “Harnessing the Mobile Revolution,” Innovation, Vol. 4, No. 1, MIT Press, Winter 2009:9–23.Google Scholar
  15. 15.
    Wireless Health 2010, (Dec 2010).
  16. 16.
    Shnayder, V., Chen, B. R., Lorincz, K., Fulford-Jones, T. R. F., and Welsh, M., “Sensor networks for medical care.” Division Eng. Appl. Sci., Harvard Univ., Cambridge, MA, Tech. Rep. TR-08-05, 2005.Google Scholar
  17. 17.
    Corventis PiiX, (Dec 2010).
  18. 18.
    CardioNet, (Dec 2010)
  19. 19.
    Halo Monitoring, (Dec 2010)
  20. 20.
    Zeo, (Dec 2010)
  21. 21.
    Seto, E., Istepanian, R. S. H., Cafazzo, J. A., Logan, A., and Sungoor, A., “UK and Canadian perspectives of the effectiveness of mobile diabetes management systems.” Annu. Int. Conf IEEE Eng. Med Bio Soc, EMBC:6584–6587, 3–6 Sept. 2009.Google Scholar
  22. 22.
    Jovanov, E., Hanish, N., Courson, V., Stidham, J., Stinson, H., Webb, C., and Denny, K., “Avatar—a Multi-sensory System for Real Time Body Position Monitoring.” Proc. of the 31th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, USA:2462–2465, September 2–6, 2009.Google Scholar
  23. 23.
    Yan, L., Zhong, L., and Jha, N., “Energy comparison and optimization of wireless body-area network technologies,” in Proc. Int. Conf. Body Area Networks (BodyNets), June 2007.Google Scholar
  24. 24.
    Yuce, M. R., Dissanayake, T., and Keong, H. C., “Wireless telemetry for electronic pill technology.” IEEE Sens.:1433–1438, 25–28 Oct. 2009.Google Scholar
  25. 25.
    Proteus Biomedical Digital Pill, (Dec 2010).
  26. 26.
    Jovanov, E., “Wireless Technology and System Integration in Body Area Networks for m—Health Applications.” Proc. 27th Ann. Int. Conf. IEEE Eng Med. Biol. Soc. Shanghai, China:7158–7160, September 2005.Google Scholar
  27. 27.
    Fensli, R., Dale, J. G., O’Reilly, P., O’Donoghue, J., Sammon, D., and Gundersen, T., “Towards Improved Healthcare Performance: Examining Technological Possibilities and Patient Satisfaction with Wireless Body Area Networks.” J. Med. Syst. 34(4):767–775.Google Scholar
  28. 28.
    AHA (2010) American Heart Association, Cardiovascular Disease Statistics,
  29. 29.
    Lloyd-Jones, D., and Members, W. G., “Heart Disease and Stroke Statistics 2009 Update: A report from the American Heart Association Statistics Committee and Statistics Subcommittee.” Circulation. 119:e21–e181, 2009.CrossRefGoogle Scholar
  30. 30.
    Rahman, M. A., Alhamid, M. F., El Saddik, A., and Gueaieb, W., “A Framework to bridge social network and body sensor network: An e-Health perspective.” IEEE Int. Conf. Multimedia Expo. ICME:1724–1727, June 28 2009–July 3 2009.Google Scholar
  31. 31.
    Xuning Tang, Yang and Christopher, C., “Identifying influential users in an online healthcare social network.” Intelligence and Security Informatics (ISI), 2010 IEEE International Conference on, vol., no.:43–48, 23–26 May 2010Google Scholar
  32. 32.
    Milenkovic, A., Otto, C., and Jovanov, E., “Wireless Sensor Networks for Personal Health Monitoring: Issues and an Implementation,” Computer Communications (Special issue: Wireless Sensor Networks: Performance, Reliability, Security, and Beyond). 29(13–14):2521–2533, August 2006.Google Scholar
  33. 33.
    Yuce, M. R., Ng, S.W. P., Myo, N. L., Lee, C. H., Khan, J. Y., and Liu, W., “A MICS band wireless body sensor network,” in Proc. IEEE WCNC.:2473–2478, 2007.Google Scholar
  34. 34.
  35. 35.
    Wong, A. C. W., McDonagh, D., Omeni, O., Nunn, C., Hernandez-Silveira, M., and Burdett, A. J., “Sensium: An Ultra-Low-Power Wireless Body Sensor Network Platform: Design & Application Challenges,” in Proc. IEEE EMBC.:6576–6579, 2009.Google Scholar
  36. 36.
    Suunto, (Dec 2010)
  37. 37.
  38. 38.
    Spectec Ant, htpp:// (Dec 2010)
  39. 39.
    Yseboodt, L., Nil, M., Huisken, J., Berekovic, M., Zhao, Q., Bouwens, F., Hulzink, J., and Meerbergen, J., “Design of 100 μW wireless sensor nodes for biomedical monitoring.” J. Signal Process. Syst. 57(1):107–119, 2009.CrossRefGoogle Scholar
  40. 40.
    Ullah, S., and Kwak, K. S., “Performance study of low-power MAC protocols for Wireless Body Area Networks,” 2010 IEEE 21st International Symposium on Personal, Indoor and Mobile Radio Communications Workshops (PIMRC Workshops).:112–116, 26–30 Sept. 2010.Google Scholar
  41. 41.
    Zhang, Y., Huang, L., Dolmans, G., and de Groot, H., “An analytical model for energy efficiency analysis of different wakeup radio schemes.” 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications.:1148–1152, 13–16 Sept. 2009.Google Scholar
  42. 42.
    Printed Batteries—Market Analysis on the Future of Printable Batteries, (Dec 2010)
  43. 43.
    Vullers, R. J. M., Schaijk, R. V., Visser, H. J., Penders, J., and Hoof, C.V., “Energy Harvesting for Autonomous Wireless Sensor Networks.” IEEE Solid-State Circuits Magazine. 2(2):29–38, Spring 2010.CrossRefGoogle Scholar
  44. 44.
    Bosch Sensortec Acceleration Sensors, (Dec 2010)
  45. 45.
    Yazicioglu, R. F., Yazicioglu, R. F., Merken, P., Puers, R., and Van Hoof, C., “A 60 μW 60 nV/√Hz readout front-end for portable biopotential acquisition systems.” IEEE J. Solid-State Circuits. 42(5):1100–1110, 2007.CrossRefGoogle Scholar
  46. 46.
    Grundlehner, B., Brown, L., Penders, J., Gyselinckx, B., “The Design and Analysis of a Real-Time, Continuous Arousal Monitor,” Proc. 6th Int. Workshop on Wearable and Implantable Body Sensor Networks, BSN 2009, June 2009:156–161.Google Scholar
  47. 47.
    Yazicioglu, R., Torfs, T., Penders, J., Romero, I., Kim, H., Merken, P., Gyselinckx, B., Yoo, H., and Van Hoof, C., “Ultra-low-power wearable biopotential sensor nodes.” Proc. EMBS.:3205–3208, Sept 2009.Google Scholar
  48. 48.
    Brown, L., van de Molengraft, J., Yazicioglu, R. F., Torfs, T., Penders, J., and Van Hoof, C., “A low-power, wireless, 8-channel EEG monitoring headset,” in Proc. IEEE EMBC.:4197–4200, 2010.Google Scholar
  49. 49.
    TI CC430, (Dec 2010)
  50. 50.
    Christakis, N. A., and Fowler, J. H., “The Spread of Obesity in a Large Social Network over 32 Years.” N. Engl. J. Med.:357:370–379, July 26, 2007.CrossRefGoogle Scholar
  51. 51.
    Warren, S., and Jovanov, E., “The Need for Rules of Engagement Applied to Wireless Body Area Networks,” IEEE Consumer Communications and Networking Conference CCNC2006, Las Vegas, Nevada:979–983, January 2006.Google Scholar
  52. 52.
    Hagler, S., Austin, D., Hayes, T. L., Kaye, J., and Pavel, M., “Unobtrusive and Ubiquitous In-Home Monitoring: A Methodology for Continuous Assessment of Gait Velocity in Elders,” IEEE Trans. Biomed. Eng. 57(4):813–820, April 2010.CrossRefGoogle Scholar
  53. 53.
    Web of Things, (Dec 2010)
  54. 54.
    Gupta, V., Poursohi, A., and Udupi, P., “Sensor. Network: An open data exchange for the web of things,” 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops):753–755, March 29 2010–April 2 2010.Google Scholar
  55. 55.
    Boulos, M. N. K., Lou, R. C., Anastasiou, A., Nugent, C. D., Alexandersson, J., Zimmermann, G., Cortes, U., and Casas, R., “Connectivity for Healthcare and Well-Being Management: Examples from Six European Projects,” Int. J. Environ. Res. Public Health. 6:1947–1971, 2009.CrossRefGoogle Scholar
  56. 56.
    Coyle, S., Lau, K. T., Moyna, N., Diamond, D., di Francesco, F., Costanzo, D., Salvo, P., Trivella, M. G., De Rossi, D., Taccini, N., Paradiso, R., Porchet, J. A., Ridolfi, A., Luprano, J., Chuzel, C., Lanier, T., Revol-Cavalier, F., Schoumaker, S., Mourier, V., Chartier, I., Convert, R., De-Monquit, H., and Bini, C., “BIOTEX—Biosensing textiles for personalised healthcare management.” IEEE Trans. Inf. Technol. Biomed. 14(2):364–370, 2010.CrossRefGoogle Scholar
  57. 57.
    K. Bourzac, “Stretchable Silicon Could Make Sports Apparel Smarter,” MIT Technology Review, Dec 9, 2010,
  58. 58.
    Mattila, E., Korhonen, I., Salminen, J., Ahtinen, A., Koskinen, E., Sarela, A., Parkka, J., and Lappalainen, R., “Empowering citizens for wellbeing and chronic disease management with wellness diary.” IEEE Trans. Inf. Technol. Biomed. 14(2):456–463, 2010.CrossRefGoogle Scholar
  59. 59.
    Dohr, A., Modre-Opsrian, R., Drobics, M., Hayn, D., and Schreier, G., “The Internet of Things for Ambient Assisted Living.” Seventh International Conference on Information Technology: New Generations (ITNG).:804–809, 2010.Google Scholar
  60. 60.
    Poon, C. C. Y., Zhang, Y. T., and Di Bao, S. D., “A novel biometrics method to secure wireless body area sensor networks for telemedicine and m-health.” IEEE Commun. Mag. 44(4):73–81, April 2006.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Electrical and Computer Engineering DepartmentUniversity of Alabama in HuntsvilleHuntsvilleUSA

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