Response Surface Optimization for Joint Contact Model Evaluation

Click name to view affiliation

Yi-Chung Lin University of Florida

Search for other papers by Yi-Chung Lin in
Current site
Google Scholar
PubMed
Close
,
Jack Farr Cartilage Restoration Center of Indiana

Search for other papers by Jack Farr in
Current site
Google Scholar
PubMed
Close
,
Kevin Carter Regeneration Technologies, Inc.

Search for other papers by Kevin Carter in
Current site
Google Scholar
PubMed
Close
, and
Benjamin J. Fregly University of Florida

Search for other papers by Benjamin J. Fregly in
Current site
Google Scholar
PubMed
Close
Restricted access

When optimization is used to evaluate a joint contact model's ability to reproduce experimental measurements, the high computational cost of repeated contact analysis can be a limiting factor. This paper presents a computationally-efficient response surface optimization methodology to address this limitation. Quadratic response surfaces were fit to contact quantities (contact force, maximum pressure, average pressure, and contact area) predicted by a discrete element contact model of the tibiofemoral joint for various combinations of material modulus and relative bone pose (i.e., position and orientation). The response surfaces were then used as surrogates for costly contact analyses in optimizations that minimized differences between measured and predicted contact quantities. The methodology was evaluated theoretically using six sets of synthetic (i.e., computer-generated) contact data, and practically using one set of experimental contact data. For the synthetic cases, the response surface optimizations recovered all contact quantities to within 3.4% error. For the experimental case, they matched all contact quantities to within 6.3% error except for maximum contact pressure, which was in error by up to 50%. Response surface optimization provides rapid evaluation of joint contact models within a limited range of relative bone poses and can help identify potential weaknesses in contact model formulation and/or experimental data quality.

Mechanical & Aerospace Engineering, 231 MAE-A Bldg.

Biomedical Engineering, University of Florida, Gainesville, FL 32611

Cartilage Restoration Center of Indiana, 1550 E. County Line Rd, Suite 200, Indianapolis, IN 46227

Regeneration Technologies Inc., 11621 Research Circle, Alachua, FL 32615.

  • Collapse
  • Expand
All Time Past Year Past 30 Days
Abstract Views 1869 98 3
Full Text Views 27 17 0
PDF Downloads 17 3 0