A Robust Parameterization of Human Gait Patterns Across Phase-Shifting Perturbations

Dario J. Villarreal, Hasan A. Poonawala, Robert D. Gregg

Research output: Contribution to journalArticlepeer-review

77 Scopus citations

Abstract

The phase of human gait is difficult to quantify accurately in the presence of disturbances. In contrast, recent bipedal robots use time-independent controllers relying on a mechanical phase variable to synchronize joint patterns through the gait cycle. This concept has inspired studies to determine if human joint patterns can also be parameterized by a mechanical variable. Although many phase variable candidates have been proposed, it remains unclear which, if any, provide a robust representation of phase for human gait analysis or control. In this paper we analytically derive an ideal phase variable (the hip phase angle) that is provably monotonic and bounded throughout the gait cycle. To examine the robustness of this phase variable, ten able-bodied human subjects walked over a platform that randomly applied phase-shifting perturbations to the stance leg. A statistical analysis found the correlations between nominal and perturbed joint trajectories to be significantly greater when parameterized by the hip phase angle (0.95+) than by time or a different phase variable. The hip phase angle also best parameterized the transient errors about the nominal periodic orbit. Finally, interlimb phasing was best explained by local (ipsilateral) hip phase angles that are synchronized during the double-support period.

Original languageEnglish
Article number7469796
Pages (from-to)265-278
Number of pages14
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume25
Issue number3
DOIs
StatePublished - Mar 2017

Bibliographical note

Publisher Copyright:
© 2001-2011 IEEE.

Keywords

  • Human gait
  • nonlinear dynamics and control
  • perturbations
  • phase

ASJC Scopus subject areas

  • Internal Medicine
  • Neuroscience (all)
  • Biomedical Engineering
  • Rehabilitation

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