Femoral strain during walking predicted with muscle forces from static and dynamic optimization
Date
2016-05-03
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Journal of Biomechanics
Abstract
Mechanical strain plays an important role in skeletal health, and the ability to accurately and noninvasively quantify bone strain in vivo may be used to develop preventive measures that improve bone quality and decrease fracture risk. A non-invasive estimation of bone strain requires combined musculoskeletal - finite element modeling, for which the applied muscle forces are usually obtained from static optimization (SO) methods. In this study, we compared finite element predicted femoral strains in walking using muscle forces obtained from SO to those obtained from forward dynamics (FD) simulation. The general trends in strain distributions were similar between FD and SO derived conditions and both agreed well with previously reported in vivo strain gage measurements. On the other hand, differences in peak maximum (εmax) and minimum (εmin) principal strain magnitudes were as high as 32% between FD (εmax/εmin=945/-1271με) and SO (εmax/εmin=752/-859με). These large differences in strain magnitudes were observed during the first half of stance, where SO predicted lower gluteal muscle forces and virtually no co-contraction of the hip adductors compared to FD. The importance of these results will likely depend on the purpose/application of the modeling procedure. If the goal is to obtain a generalized strain distribution for adaptive bone remodeling algorithms, then traditional SO is likely sufficient. In cases were strain magnitudes are critical, as is the case with fracture risk assessment, bone strain estimation may benefit by including muscle activation and contractile dynamics in SO, or by using FD when practical.
Description
Keywords
Biomechanics, Bone, Finite element model, Mechanical Loading, Musculoskeletal model
Citation
Edwards, W. Brent, Ross H. Miller, and Timothy R. Derrick. "Femoral strain during walking predicted with muscle forces from static and dynamic optimization." Journal of biomechanics 49.7 (2016): 1206-1213.