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Abstract

Falls are a major health risk that diminishes the quality of life among older people and increases the health services cost. Reliable and earlier prediction of an increased fall risk is essential to improve its prevention, aiming to avoid the occurrence of falls. In this paper, we propose the use of mobile phones as a platform for developing a fall prediction system by running an inertial sensor based fall prediction algorithm. Experimental results of the system, which we still consider as work in progress, are encouraging making us optimistic regarding the feasibility of a reliable phone-based fall predictor, which can be of great value for older persons and society.

Keywords

Fall Prevention Fall Risk Prediction Inertial Sensors Older people Gait analysis Smartphone 

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References

  1. 1.
    National Institute for Health Excellence and Clinical: Clinical practice guideline for the assessment and prevention of falls in older people (CG21), vol. 2. Royal College of Nursing, London (2004)Google Scholar
  2. 2.
    King, R.C., Atallah, L., Wong, C., Miskelly, F., Yang, G.Z.: Elderly Risk Assessment of Falls with BSN. In: 2010 International Conference on Body Sensor Networks, pp. 30–35 (2010)Google Scholar
  3. 3.
    Ganz, D.A., Bao, Y., Shekelle, P.G., Rubenstein, L.Z.: Will my patient fall? The Journal of the American Medical Association 297(1), 77–86 (2007)CrossRefGoogle Scholar
  4. 4.
    Narayanan, M.R., Redmond, S.J., Scalzi, M.E., Lord, S.R., Celler, B.G., Lovell, N.H.: Longitudinal falls-risk estimation using triaxial accelerometry. IEEE Transactions on Bio-Medical Engineering 57(3), 534–541 (2010)CrossRefGoogle Scholar
  5. 5.
    Montero-Odasso, M., Schapira, M., Soriano, E.R., Varela, M., Kaplan, R., Camera, L.A., Mayorga, L.M.: Gait velocity as a single predictor of adverse events in healthy seniors aged 75 years and older. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences 60(10), 1304–1309 (2005)CrossRefGoogle Scholar
  6. 6.
    Laessoe, U., Hoeck, H.C., Simonsen, O., Sinkjaer, T., Voigt, M.: Fall risk in an active elderly population–can it be assessed? Journal of Negative Results in Biomedicine 6(2) (2007)Google Scholar
  7. 7.
    Senden, R., Grimm, B., Heyligers, I.C., Savelberg, H., Meijer, K.: Acceleration-based gait test for healthy subjects: reliability and reference data. Gait & Posture 30(2), 192–196 (2009)CrossRefGoogle Scholar
  8. 8.
    Bogin, B., Varela-Silva, M.I.: Leg length, body proportion, and health: a review with a note on beauty. International Journal of Environmental Research and Public Health 7(3), 1047–1075 (2010)CrossRefGoogle Scholar
  9. 9.
    Zijlstra, W.: Assessment of spatio-temporal parameters during unconstrained walking. European Journal of Applied Physiology 92, 39–44 (2004)CrossRefGoogle Scholar
  10. 10.
    Alvarez, D., Gonzalez, R.C., Lopez, A., Alvarez, J.C.: Comparison of Step Length Estimators from Wearable Accelerometer Devices. In: Proceedings of the 28th IEEE EMBS Annual International Conference, New York City, USA, pp. 5964–5967 (2006)Google Scholar
  11. 11.
    Verghese, J., Holtzer, R., Lipton, R.B., Wang, C.: Quantitative gait markers and incident fall risk in older adults. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences 64(8), 896–901 (2009)CrossRefGoogle Scholar
  12. 12.
    Culhane, K.M., O’Connor, M., Lyons, D., Lyons, G.M.: Accelerometers in rehabilitation medicine for older adults. Age and Ageing 34(6), 556–560 (2005)CrossRefGoogle Scholar
  13. 13.
    Wu, G., Cavanagh, P.R.: ISB Recommendations in the Reporting for Standardization of Kinematic Data. Journal of Biomechanics 28(10), 1257–1261 (1995)CrossRefGoogle Scholar
  14. 14.
    Slifka, L.D.: An Accelerometer based approach to measuring displacement of a vehicle body. PhD thesis, Horace Rackham School of Graduate Studies of the University of Michigan (2004)Google Scholar
  15. 15.
    Réseau Francophone de Prévention des Traumatismes et de Promotion de la Sécurité. Good Practice Guide - Prevention of falls in the elderly living at home. Éditions inpes (2005)Google Scholar
  16. 16.
    Graf, C.: The Lawton Instrumental Activities of Daily Living Scale. American Journal of Nursing 108(4), 52–62 (2008)CrossRefGoogle Scholar
  17. 17.
    Hill, K.: Activities-specific and Balance Confidence (ABC) Scale. Australian Journal of Physiotherapy 51(3), 197 (2005)CrossRefGoogle Scholar
  18. 18.
    Society of Hospital Medicine. Website (2011), http://www.hospitalmedicine.org/

Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2012

Authors and Affiliations

  • Vânia Guimarães
    • 1
  • Pedro M. Teixeira
    • 1
  • Miguel P. Monteiro
    • 2
  • Dirk Elias
    • 1
  1. 1.Fraunhofer AICOS PortugalPortoPortugal
  2. 2.Faculdade de Engenharia da Universidade do PortoPortoPortugal

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