• DocumentCode
    3073057
  • Title

    Fall-detection through vertical velocity thresholding using a tri-axial accelerometer characterized using an optical motion-capture system

  • Author

    Bourke, Alan K. ; Donovan, Karol J O ; Nelson, John ; ÓLaighin, Gearóid M.

  • Author_Institution
    Wireless Access Research Centre, Department of Electronic and Computer Engineering, University of Limerick, Ireland
  • fYear
    2008
  • fDate
    20-25 Aug. 2008
  • Firstpage
    2832
  • Lastpage
    2835
  • Abstract
    Falls in the elderly population are a major problem for today´s society. The immediate automatic detection of such events would help reduce the associated consequences of falls. This paper describes the development of an accurate, accelerometer-based fall detection system to distinguish between Activities of Daily Living (ADL) and falls. It has previously been shown that falls can be distinguished from normal ADL through vertical velocity thresholding using an optical motion capture system. In this study however accurate vertical velocity profiles of the trunk were generated by simple signal processing of the signals from a tri-axial accelerometer (TA).
  • Keywords
    Accelerometers; Inertial confinement; Injuries; Optical recording; Optical sensors; Optical signal processing; Senior citizens; Sensor systems; Signal processing algorithms; Wearable sensors; Acceleration; Accidental Falls; Adult; Algorithms; Biomechanics; Clothing; Equipment Design; Humans; Image Interpretation, Computer-Assisted; Male; Materials Testing; Models, Statistical; Monitoring, Ambulatory; Movement; Reproducibility of Results;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-1814-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2008.4649792
  • Filename
    4649792