Abstract
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 language | English (US) |
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Article number | 5711650 |
Pages (from-to) | 1715-1723 |
Number of pages | 9 |
Journal | IEEE Transactions on Biomedical Engineering |
Volume | 58 |
Issue number | 6 |
DOIs | |
State | Published - Jun 2011 |
Funding
Manuscript received October 5, 2010; accepted January 8, 2011. Date of publication February 10, 2011; date of current version May 18, 2011. This work was supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC) and in part by the Canadian Institutes of Health Research (CIHR). Asterisk indicates corresponding author.
Keywords
- Biological system modeling
- joint stiffness
- time-varying (TV) systems
ASJC Scopus subject areas
- Biomedical Engineering