Identification of time-varying intrinsic and reflex joint stiffness

Daniel Ludvig*, Tanya Starret Visser, Heidi Giesbrecht, Robert E. Kearney

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

47 Scopus citations


Dynamic joint stiffness defines the dynamic relationship between the position of a joint and the torque acting about it and can be separated into intrinsic and reflex components. Under stationary conditions, these can be identified using a nonlinear parallel-cascade algorithm that models intrinsic stiffnessa linear dynamic response to positionand reflex stiffnessa nonlinear dynamic response to velocityas parallel pathways. Experiments using this method show that both intrinsic and reflex stiffness depend strongly on the operating point, defined by position and torque, likely because of some underlying nonlinear behavior not modeled by the parallel-cascade structure. Consequently, both intrinsic and reflex stiffness will appear to be time-varying whenever the operating point changes rapidly, as during movement. This paper describes and validates an extension of the parallel-cascade algorithm to time-varying conditions. It describes the ensemble method used to estimate time-varying intrinsic and reflex stiffness. Simulation results demonstrate that the algorithm can track rapid changes in joint stiffness accurately. Finally, the performance of the algorithm in the presence of noise is tested. We conclude that the new algorithm is a powerful new tool for the study of joint stiffness during functional tasks.

Original languageEnglish (US)
Article number5711650
Pages (from-to)1715-1723
Number of pages9
JournalIEEE Transactions on Biomedical Engineering
Issue number6
StatePublished - Jun 2011


  • Biological system modeling
  • joint stiffness
  • time-varying (TV) systems

ASJC Scopus subject areas

  • Biomedical Engineering


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