Author(s): Lindemann U, Hock A, Stuber M, Keck W, Becker C
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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, which was fixed behind the ear. The sensitivity of the fall detection was assessed by 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 sum-vector of velocity of all spatial components right before the impact higher than 0.7 m s(-1); and the sum-vector of acceleration of all spatial components higher than 6 g. 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.
This article was published in Med Biol Eng Comput
and referenced in International Journal of Neurorehabilitation