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Muscle Activation Variability Is Inversely Correlated with Walking Speed

  • F. DzeladiniEmail author
  • A. Grappe
  • C. Simpson
  • A. R. Wu
  • A. Ijspeert
Conference paper
Part of the Biosystems & Biorobotics book series (BIOSYSROB, volume 15)

Abstract

Individuals with motor impairments typically walk at much slower speeds than their unimpaired counterparts, yet their gait data is still evaluated against the relatively faster gait of healthy subjects. Therefore a good understanding of unimpaired gait at extremely slow speeds is needed for comparison. Studies have shown that walking at very slow speeds is quantitatively different from self-selected walking speed. These modifications can be observed at different levels (kinetic, kinematic, electromyographic). In order to better understand the changes in walking at extremely slow speeds, we recorded seven subjects walking at their preferred speed and at speeds ranging from 0.11 m/s to 0.61 m/s. In this study, we analyzed changes in muscle activations and quantified their variability using the Pearson correlation coefficient. Confirming previous observation, we show that both the inter- and intra-subject variability of muscle activities increases with decreases in walking speed, with a more pronounced effect for proximal muscles. The inter-subject correlation of muscle activities also suggests a modular organization of muscle activities in three functional blocks at normal speed. This modular organization vanishes with decreasing walking speed following a proximo-distal gradient.

Notes

Acknowledgments

The work performed as part of the SYMBITRON project, supported by EU research program FP7, FET-Proactive initiative “Symbiotic human-machine interaction” (ICT-2013-10) under project contract #611626.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • F. Dzeladini
    • 1
    • 2
    Email author
  • A. Grappe
    • 1
    • 2
  • C. Simpson
    • 1
    • 2
  • A. R. Wu
    • 1
    • 2
  • A. Ijspeert
    • 1
    • 2
  1. 1.Biorobotics Laboratory of the Ecole Polytechnique Federale de LausanneLausanneSwitzerland
  2. 2.Mechanical Engineering DepartmentStanford UniversitySan FranciscoUSA

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