Medical and Biological Engineering and Computing

, Volume 43, Issue 5, pp 548–551 | Cite as

Evaluation of a fall detector based on accelerometers: A pilot study

  • U. Lindemann
  • A. Hock
  • M. Stuber
  • W. Keck
  • C. Becker
Article

Abstract

As falls and fall-related injuries remain a major challenge in the public health domain, reliable and immediate detection of falls is important so that adequate medical support can be delivered. Available home alarm systems are placed on the hip, but have several shortcomings. A fall detector based on accelerometers and placed at head level was developed, as well as an algorithm able to distinguish between activities of daily living and simulated falls. Accelerometers were integrated into a hearing-aid housing, investigation into the acceleration patterns of the head of a young volunteer during intentional falls. The specificity was assessed by investigation into activities of daily living of the same volunteer. In addition, a healthy elderly woman (83 years) wore the sensor during the day. Three trigger thresholds were identified so that a fall could be recognised: the sum-vector of acceleration in the xy-plane higher than 2 g; the sumvector of velocity of all spatial components right before the impact higher than 0.7ms−1; and the sum-vector of acceleration of all spatial components higher than 6g. The algorithm was able to discriminate activities of daily living from intentional falls. Thus high sensitivity and specificity of the algorithm could be demonstrated that was better than in other fall detectors worn at the hip or wrist at the same stage of development.

Keywords

Accelerometers Accidental falls Fall detector 

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Copyright information

© IFMBE 2005

Authors and Affiliations

  • U. Lindemann
    • 1
    • 2
  • A. Hock
    • 3
  • M. Stuber
    • 3
  • W. Keck
    • 3
  • C. Becker
    • 1
  1. 1.Department of Geriatric RehabilitationRobert-Bosch-KrankenhausStuttgartGermany
  2. 2.Bethesda Geriatric Hospital UlmAcademic Centre at the University of UlmUlmGermany
  3. 3.Laboratory of Data Processing in MedicineUniversity of Applied Science UlmUlmGermany

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