Advertisement

Sensors for Individual Ability (Implicit Data)

  • Bruce R. Schatz
  • Richard B. BerlinJr.
Chapter
Part of the Health Informatics book series (HI)

Abstract

Sensors are implicit measurements, in that they gather data automatically from the person or from the environment. This is as opposed to explicit, where the person must manually answer a question from a questionnaire or enter an observation into a diary. Implicit measurement has an advantage in being able to gather more data, however there is always the issue of to what extent the data gathered is actionable. It is technically possible to measure every step a person takes or to measure every location a person moves to. But what would be done with such data to enable useful health management? Most measurements today mimic what is most effective for acute care, while chronic care or everyday health may be radically different.

Keywords

Mobile Device Chronic Care Implicit Measurement Home Equivalent Total Volatile Organic Compound 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 37.
    Buchanan M. The science of subtle signals. Strategy + Business. 2007;48:1-9. http://web.media.mit.edu/~sandy/Honest-Signals-sb48_07307.pdf.Google Scholar
  2. 47.
    Chen N, Lee Y, Rabb M, Schatz B. Toward Dietary Assessment via Mobile Phone Video Cameras, American Medical Informatics Association (AMIA) Annual Symposium; November, 2010; Washington DC: 5.Google Scholar
  3. 50.
    Christakis N, Fowler J. The spread of obesity in a large social network over 32 years. N Engl J Med. 2007;357(4):370-379.PubMedCrossRefGoogle Scholar
  4. 58.
    Cooper K. Aerobics. New York: Bantam paperback; 1980.Google Scholar
  5. 67.
    Dishongh T, McGrath M. Wireless Sensor Networks for Healthcare Applications. Boston: Artech House; 2010; Intel Healthcare.Google Scholar
  6. 117.
    Intel Healthcare. Collaborative Research Initiatives in People-Centered Healthcare. http://www.intel.com/about/companyinfo/healthcare/people/research/approach.htm.
  7. 135.
    Kientz J, Patel S, Jones B, et al. The Georgia Tech Aware Home, Human Factors in Computing Systems (CHI), Florence, Italy, April, 3675-3680; 2008.Google Scholar
  8. 154.
    Marmot M. Multilevel approaches to understanding social determinants. In: Berkman L, Kawachi I, eds. Social Epidemiology. New York: Oxford University Press; 2000; chap 15, [Ref 18].Google Scholar
  9. 166.
    NAS. Recommended Dietary Allowances. 8th ed. Washington, DC: National Academy of Sciences; 1974.Google Scholar
  10. 169.
    Nolan K, Heslin J. The Calorie Counter. 5th ed. New York: Simon & Schuster; 2009.Google Scholar
  11. 181.
    Pentland S. Healthwear: medical technology becomes wearable. IEEE Computer. 2004;37(5):42-49.Google Scholar
  12. 182.
    Pentland S. Honest Signals: How They Shape Our World. Cambridge MA: MIT Press; 2010.Google Scholar
  13. 184.
    Philips Research Technologies – Ambient Intelligence. http://www.research.philips.com/technologies/projects/ami/background.html
  14. 185.
  15. 236.
    Smith J, Schatz B. Feasibility of Mobile Phone Based Management of Chronic Illness, American Medical Informatics Association (AMIA) Annual Symposium; November, 2010; Washington DC: 5.Google Scholar
  16. 259.
    United States Department Agriculture. Handbook of the Nutritional Contents of Foods, New York: Dover Publications; 1963, 1975 reprint, Prepared by Watt B and Merrill A.Google Scholar
  17. 261.
    Varshney U. Pervasive Healthcare Computing: EMR/EHR, Wireless and Health Monitoring. New York: Springer; 2009.CrossRefGoogle Scholar
  18. 270.
    Web (2007 WellnessPhone). Wellness Mobile Phone Measures Body Fat, Pulse, Nikkei Electronics Asia, October 4, 2007. http://techon.nikkeibp.co.jp/english/NEWS_EN/20071004/140249/.
  19. 271.
    Web (2008 Asthma). Asthma Attack: Vest-Based Sensors Monitor Environmental Exposure to Help Understand Causes, Science Daily, January 25, 2008. http://www.sciencedaily.com/releases/2008/01/080122154626.htm.
  20. 272.
    Web (2008 DoCoMo). New Health Phones from Fujitsu and NTT DoCoMo, Japan Trends, July 31, 2008. http://www.japantrends.com/new-health-phones-from-fujitsu-and-ntt-docomo/.
  21. 273.
    Web (2008 Firefighter). Physiologists create Undergarment to Measure Vital Signs of Firefighters, Science Daily, February 1, 2008. www.sciencedaily.com/videos/2008/0212-vitals_vest.htm.
  22. 275.
    Web (2009 Corventis). Corventis Launches AVIVO Mobile Patient Management System, Diagnostic and Interventional Cardiology, April 22, 2009. www.dicardiology.net/node/32241/3.
  23. 276.
    Web (2009 Pacemaker). World’s first ‘wireless’ pacemaker talks to your doctor daily, whether you like it or not (though you probably do), Engadget, August 11, 2009. www.engadget.com/2009/08/11/worlds-first-wireless-pacemaker-talks-to-your-doctor-daily-w/
  24. 277.
    Web (2009 Philips). Philips’ New Body Monitoring System, The Future of Things, August 10, 2009. http://thefutureofthings.com/pod/7894/philips-new-health-monitoring-system.html.
  25. 281.
  26. 282.
    Web MyHeart. MyHeart Project Technical Objectives. http://www.hitech-projects.com/euprojects/myheart/en/objectives.html.

Copyright information

© Springer-Verlag London limited 2011

Authors and Affiliations

  • Bruce R. Schatz
    • 1
  • Richard B. BerlinJr.
    • 1
  1. 1.Department of Medical Information Science, Department of Computer ScienceUniversity of Illinois at Urbana-ChampaignUrbanaUSA

Personalised recommendations