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Smart Shoe-Based Evaluation of Gait Phase Detection Accuracy Using Body-Worn Accelerometers

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Wireless Mobile Communication and Healthcare (MobiHealth 2017)

Abstract

The spatio-temporal parameters of gait can reveal early signs of medical conditions affecting motor ability, including the frailty syndrome and neurodegenerative diseases. This has brought increasing interest into the development of wearable-based systems to automatically estimate the most relevant gait parameters, such as stride time and the duration of gait phases. The aim of this paper is to investigate the use of body-worn accelerometers at different positions as a means to continuously analyze gait. We relied on a smart shoe to provide the ground truth in terms of reliable gait phase measurements, so as to achieve a better understanding of the signal captured by body-worn sensors even during longer walks. A preliminary experiment shows that both trunk and thigh positions achieve accurate results, with a mean absolute error in the estimation of gait phases of \(\sim \)12 ms and \(\sim \)31 ms, respectively.

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Notes

  1. 1.

    Some other works refer to heel-strike and toe-off as initial foot contact (IC) and final foot contact (FC) gait events, respectively.

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Authors and Affiliations

  1. Dipartimento di Ingegneria dell’Informazione, University of Pisa, Largo Lucio Lazzarino 1, 56122, Pisa, Italy

    Marco Avvenuti, Nicola Carbonaro, Mario G. C. A. Cimino, Guglielmo Cola, Alessandro Tognetti & Gigliola Vaglini

  2. Research Center “E. Piaggio”, University of Pisa, Largo Lucio Lazzarino 1, 56122, Pisa, Italy

    Nicola Carbonaro & Alessandro Tognetti

Authors
  1. Marco Avvenuti
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  2. Nicola Carbonaro
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  3. Mario G. C. A. Cimino
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  4. Guglielmo Cola
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  5. Alessandro Tognetti
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  6. Gigliola Vaglini
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Corresponding author

Correspondence to Guglielmo Cola .

Editor information

Editors and Affiliations

  1. Polytechnic University of Milan, Milan, Italy

    Paolo Perego

  2. University of California, Irvine, California, USA

    Amir M. Rahmani

  3. ICT, Institute of Computer Technology, Vienna University of Technology, Vienna, Austria

    Nima TaheriNejad

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Avvenuti, M., Carbonaro, N., Cimino, M.G.C.A., Cola, G., Tognetti, A., Vaglini, G. (2018). Smart Shoe-Based Evaluation of Gait Phase Detection Accuracy Using Body-Worn Accelerometers. In: Perego, P., Rahmani, A., TaheriNejad, N. (eds) Wireless Mobile Communication and Healthcare. MobiHealth 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 247. Springer, Cham. https://doi.org/10.1007/978-3-319-98551-0_29

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  • DOI: https://doi.org/10.1007/978-3-319-98551-0_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98550-3

  • Online ISBN: 978-3-319-98551-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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