Parameterizing Human Locomotion across Quasi-Random Treadmill Perturbations and Inclines

Rebecca Macaluso*, Kyle Embry, Dario J. Villarreal, Robert D. Gregg

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Previous work has shown that it is possible to use a mechanical phase variable to accurately quantify the progression through a human gait cycle, even in the presence of disturbances. However, mechanical phase variables are highly dependent on the behavior of the body segment from which they are measured, which can change with the human's task or in response to different disturbances. In this study, we compare kinematic parameterization methods based on time, thigh phase angle, and tibia phase angle with motion capture data obtained from ten able-bodied subjects walking at three inclines while experiencing phase-shifting perturbations from a split-belt instrumented treadmill. The belt, direction, and timings of perturbations were quasi-randomly selected to prevent anticipatory action by the subjects and sample different types of perturbations. Statistical analysis revealed that both phase parameterization methods are superior to time parameterization, with thigh phase angle also being superior to tibia phase angle in most cases.

Original languageEnglish (US)
Article number9350301
Pages (from-to)508-516
Number of pages9
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
StatePublished - 2021


  • Human locomotion
  • inclined walking
  • perturbations
  • prosthetic limbs

ASJC Scopus subject areas

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


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