Understanding Modulation of Ankle Stiffness During Stance Phase of Walking on Different Ground Surfaces

Varun Nalam, Clayton Bliss, Joshua B. Russell, Omik Save, Hyunglae Lee

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Understanding how human ankle mechanics are modulated when walking on various ground surfaces (e.g., soft and unstable ground surfaces) would help the development of controllers of lower extremity robots (e.g., prostheses and exoskeletons) mimicking human ankle behaviors. With this goal in mind, this study investigated how ankle stiffness in the sagittal plane is modulated throughout the stance phase of walking over different ground surfaces. A robotic platform, capable of simulating different mechanical environments, was used to quantify ankle stiffness in the sagittal plane during walking over compliant and rigid surfaces. The group average results of 10 healthy individuals showed that ankle stiffness increased with the progression of stance phase of walking but there was no significant environmental effect on the stiffness modulation. Further investigation into each individual subject revealed that surface compliance had an impact on the modulation of ankle stiffness in the later stance phase, which was significantly correlated with center of pressure position regardless of the surface condition (Pearson correlation coefficient: ∼0.93). Implications of the observed results for the development of continuous impedance controllers for lower extremity robots are discussed.

Original languageEnglish (US)
Pages (from-to)9294-9301
Number of pages8
JournalIEEE Robotics and Automation Letters
Issue number4
StatePublished - Oct 1 2022


  • Ankle impedance
  • assistive robotics
  • impedance control
  • interaction control
  • lower extremity robots

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence


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