The Role of MHealth and Wearables for Anticipation in Medicine

  • Alice FerngEmail author
  • Vishal PunwaniEmail author
  • Shiv Gaglani


As the market for health-tracking wearable devices continues to expand, there is an emerging niche for healthcare applications, and data acquisition and usage. Within this area exists a wealth of clinically relevant data already collected from wearers, including physiological and lifestyle data. This information allows us to not only optimize current medical treatments and health planning, but also to expand preventive medicine by applying anticipation to medicine. We propose that much of the data collected through these wearable devices can be used to inform both patient and clinician of long-term physiological trends, and to anticipate potential onset of illnesses with a view to stemming their progression, or even mitigating their occurrence altogether. This paper highlights important issues within the health-wearable paradigm and presents upcoming applications of wearable technologies in medicine.


Mhealth Tracking Wearables Technology Anticipation Prevention 


  1. 1.
    Gaglani, S.M., Topol, E.J.: iMedEd: the role of mobile health technologies in medical education. Acad. Med. 89(9), 1207–1209 (2014). doi: 10.1097/ACM.0000000000000361 CrossRefGoogle Scholar
  2. 2.
    Quinn, C.C., Clough, S.S., Minor, J.M. et al.: WellDoc™ mobile diabetes management randomized controlled trial: change in clinical and behavioral outcomes and patient and physician satisfaction (2008)Google Scholar
  3. 3.
    Steinhubl, S.R., Muse, E.D., Topol, E.J.: Can mobile health technologies transform health care? JAMA 310, 2395–2396 (2013). doi: 10.1001/jama.2013.281078 CrossRefGoogle Scholar
  4. 4.
    Hooge, A. (ed.): Five predictions for the future of wearables. (2015)Google Scholar
  5. 5.
    Nadin, M.: Can predictive computation reach the level of anticipatory computing? Int. J. Appl. Res. Inf. Technol. Comput. 5, 171–200 (2014). doi: 10.5958/0975-8089.2014.00011.6 CrossRefGoogle Scholar
  6. 6.
    Sullivan, J.E.: Clinical trial endpoints. FDA Clinical Investigator Training Course (2012)Google Scholar
  7. 7.
    John Hancock Introduces as Whole New Approach to Life Insurance in the U.S. That Rewards Customers for Healthy Living. PR Newswire (2015)Google Scholar
  8. 8.
    Lecklider, T. (ed.): Powering medical haute couture. Eval. Eng. (2015)Google Scholar
  9. 9.
    Marbury, D. (ed.): 10 Apple HealthKit mobile apps for physicians and their patients. Med. Econ. (2014)Google Scholar
  10. 10.
    Lang, M.B. (ed.): What if Apple were an ACO? HealthCare Purchasing News (2015)Google Scholar
  11. 11.
    Peek, S.T.M., Wouters, E.J.M., van Hoof, J., et al.: Factors influencing acceptance of technology for aging in place: a systematic review. Int. J. Med. Inf. 83, 235–248 (2014). doi: 10.1016/j.ijmedinf.2014.01.004 CrossRefGoogle Scholar
  12. 12.
    Dehzad, F., Hilhorst, C., de Bie, C., Claassen, E.: Adopting health apps, what’s hindering doctors and patients? Health (2014). doi: 10.4236/health.2014.616256 Google Scholar
  13. 13.
    What Does it Mean for FDA to “Classify” a Medical Device? Center for Devices, Health RGoogle Scholar
  14. 14.
    Lyons, E.J., Lewis, Z.H., Mayrsohn, B.G., Rowland, J.L.: Behavior change techniques implemented in electronic lifestyle activity monitors: a systematic content analysis. J. Med. Internet Res. 16(e192) (2014). doi: 10.2196/jmir.3469
  15. 15.
    Fogg, B.J. (ed.): What causes behavior change? (2015)Google Scholar
  16. 16.
    Gaglani, S.M. (ed.): A glimpse into the Smartphone physical. MedGadget (2013)Google Scholar
  17. 17.
    Gaglani, S.M., Batista, M.A.: The future of Smartphones in health care. Virtual Mentor 15, 947 (2013). doi: 10.1001/virtualmentor.2013.15.11.stas1-1311 CrossRefGoogle Scholar
  18. 18.
    Preventice announces commercial availability of BodyGuardian remote patient monitoring system. J. Innovations Card. Rhythm Manage. (2015)Google Scholar
  19. 19.
    Muhlestein, J.B.: QTC intervals can be assessed with the AliveCor heart monitor in patients on Dofetilide for atrial fibrillation. J. Electrocardiol. 48, 10–11 (2015). doi: 10.1016/j.jelectrocard.2014.11.007 CrossRefGoogle Scholar
  20. 20.
    Tarakji, K.G., Wazni, O.M., Callahan, T., et al.: Using a novel wireless system for monitoring patients after the atrial fibrillation ablation procedure: the iTransmit study. Heart Rhythm 12, 554–559 (2015). doi: 10.1016/j.hrthm.2014.11.015 CrossRefGoogle Scholar
  21. 21.
    Jabr, F.: Are we too close to making Gattaca a reality? In: Are We Too Close to Making Gattaca a Reality? (2013) Accessed 6 Sept 2015

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.University of Arizona College of MedicineTucsonUSA
  2. 2.University of Melbourne School of MedicineMelbourneAustralia
  3. 3.Johns Hopkins School of MedicineBaltimoreUSA

Personalised recommendations