• DocumentCode
    2946621
  • Title

    Elderly Risk Assessment of Falls with BSN

  • Author

    King, R.C. ; Atallah, L. ; Wong, C. ; Miskelly, F. ; Yang, G.-Z.

  • Author_Institution
    Dept. of Comput., Imperial Coll. London, London, UK
  • fYear
    2010
  • fDate
    7-9 June 2010
  • Firstpage
    30
  • Lastpage
    35
  • Abstract
    Due to the natural aging process, the risks associated with falling can increase significantly. For the elderly, this usually marks a rapid deterioration of their health. While there are identified strategies that can be adopted to reduce the number of falls, it is still not possible to prevent all falls. Clinically, the Tinetti Gait and Balance Assessment has been widely used to assess the risk of falls in elderly by examining balance and gait. This paper presents our initial results of using an ear-worn BSN sensor to detect aspects of the Tinetti Gait and Balance Assessment to predict the risk of falls compared to a healthy control cohort. For this study, data was collected from a control cohort of 12 healthy volunteers and a cohort of 16 elderly fallers of varying degrees of risk. The results derived have shown that it is possible to directly detect some aspects of the Tinetti Gait and Balance Assessment and the Timed Up and Go test, demonstrating the potential value of using the platform for continuous assessment in a home environment.
  • Keywords
    body sensor networks; gait analysis; geriatrics; mechanoception; BSN; Tinetti Gait and Balance Assessment; balance; elderly risk assessment; gait; natural aging; Accelerometers; Aging; Body sensor networks; Educational institutions; Hazards; Medical services; Musculoskeletal system; Risk management; Senior citizens; Testing; Body Sensor Networks; balance assessment; elderly faller;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Body Sensor Networks (BSN), 2010 International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-5817-2
  • Type

    conf

  • DOI
    10.1109/BSN.2010.42
  • Filename
    5504810