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    An analytical comparison of datasets of Real-World and simulated falls intended for the evaluation of wearable fall alerting systems

    • Autor
      Casilari-Pérez, EduardoAutoridad Universidad de Málaga
    • Fecha
      2022-10
    • Editorial/Editor
      Elsevier
    • Palabras clave
      AccelerometerDatasetWearable device; Sistemas informáticos
    • Resumen
      Automatic fall detection is one of the most promising applications of wearables in the field of mobile health. The characterization of the effectiveness of wearable fall detectors is hampered by the inherent difficulty of testing these devices with real-world falls. In fact, practically all the proposals in the literature assess the detection algorithms with ‘scripted’ falls that are simulated in a controlled laboratory environment by a group of volunteers (normally young and healthy participants). Aiming at appraising the adequacy of this method, this work systematically compares the statistical characteristics of the acceleration signals from two databases with real falls and those computed from the simulated falls provided by 18 well-known repositories commonly employed by the related works. The results show noteworthy differences between the dynamics of emulated and real-life falls, which undermines the testing procedures followed to date and forces to rethink the strategies for evaluating wearable fall detectors.
    • URI
      https://hdl.handle.net/10630/24944
    • DOI
      https://dx.doi.org/https://doi.org/10.1016/j.measurement.2022.111843
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    1-s2.0-S0263224122010429-main.pdf (952.3Kb)
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    REPOSITORIO INSTITUCIONAL UNIVERSIDAD DE MÁLAGA
    REPOSITORIO INSTITUCIONAL UNIVERSIDAD DE MÁLAGA
     

     

    REPOSITORIO INSTITUCIONAL UNIVERSIDAD DE MÁLAGA
    REPOSITORIO INSTITUCIONAL UNIVERSIDAD DE MÁLAGA