Sensitivity of predicted muscle forces during gait to anatomical variability in musculotendon geometry.

Scaled generic musculoskeletal models are commonly used to drive dynamic simulations of motions. It is however, acknowledged that not accounting for variability in musculoskeletal geometry and musculotendon parameters may confound the simulation results, even when analysing control subjects. This study documents the three-dimensional anatomical variability of musculotendon origins and insertions of 33 lower limb muscles determined based on magnetic resonance imaging in six subjects.

A new method for estimating subject-specific muscle-tendon parameters of the knee joint actuators: a simulation study.

A new method for the estimation of subject-specific muscle-tendon parameters of the knee actuators based on dynamometry experiments is presented. The algorithm aims at estimating the tendon slack length and the optimal muscle fiber length by minimizing the difference between experimentally reproduced and model-based joint moments. The key innovative features are as follows: (i) the inclusion of a priori physiological knowledge to define a physiologically feasible set, the hot start for the optimization, and constraints for the optimization and (ii) the introduction of a new (affine) transformation of the muscle-tendon parameters, which greatly improves the numerical condition of the optimization.

An extended dynamometer setup to improve the accuracy of knee joint moment assessment.

This paper analyzes an extended dynamometry setup that aims at obtaining accurate knee joint moments. The main problem of the standard setup is the misalignment of the joint and the dynamometer axes of rotation due to nonrigid fixation, and the determination of the joint axis of rotation by palpation. The proposed approach 1) combines 6-D registration of the contact forces with 3-D motion capturing (which is a contribution to the design of the setup); 2) includes a functional axis of rotation in the model to describe the knee joint (which is a contribution to the modeling); and 3) calculates joint moments by a model-based 3-D inverse dynamic analysis.