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Computational evaluation of load carriage effects on gait balance stability

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  • Carlotta Mummolo
  • Sukyung Park
  • Luigi Mangialardi
  • Joo H. Kim

Abstract

Evaluating the effects of load carriage on gait balance stability is important in various applications. However, their quantification has not been rigorously addressed in the current literature, partially due to the lack of relevant computational indices. The novel Dynamic Gait Measure (DGM) characterizes gait balance stability by quantifying the relative effects of inertia in terms of zero-moment point, ground projection of center of mass, and time-varying foot support region. In this study, the DGM is formulated in terms of the gait parameters that explicitly reflect the gait strategy of a given walking pattern and is used for computational evaluation of the distinct balance stability of loaded walking. The observed gait adaptations caused by load carriage (decreased single support duration, inertia effects, and step length) result in decreased DGM values (p < 0.0001), which indicate that loaded walking motions are more statically stable compared with the unloaded normal walking. Comparison of the DGM with other common gait stability indices (the maximum Floquet multiplier and the margin of stability) validates the unique characterization capability of the DGM, which is consistently informative of the presence of the added load.

Suggested Citation

  • Carlotta Mummolo & Sukyung Park & Luigi Mangialardi & Joo H. Kim, 2016. "Computational evaluation of load carriage effects on gait balance stability," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 19(11), pages 1127-1136, August.
  • Handle: RePEc:taf:gcmbxx:v:19:y:2016:i:11:p:1127-1136
    DOI: 10.1080/10255842.2015.1110146
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    Cited by:

    1. Fabio De Felice & Laura Petrillo & Luigi Ranieri & Antonella Petrillo, 2019. "Previous Studies and Differences Between Lean Management and World Class Manufacturing," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(06), pages 1941-1966, November.
    2. Facchini, F. & Digiesi, S. & Mossa, G., 2020. "Optimal dry port configuration for container terminals: A non-linear model for sustainable decision making," International Journal of Production Economics, Elsevier, vol. 219(C), pages 164-178.

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