ARUP; ISBN: 978-0-9562121-5-3 - CMBBE 2012 - Cardiff University

FORWARD DYNAMICS MOVEMENT SIMULATION WITH
ANATOMICAL REPRESENTATION OF THE KNEE
1. ABSTRACT
Trent M. Guess 1
The absence of detailed knowledge regarding mechanical loading on joint structures
inhibits our understanding of joint degeneration and injury. This work combines muscle
driven forward dynamics movement simulations with anatomical joint models for
simultaneous prediction of muscle force and joint loading. The models are developed in
the multi-body framework and the natural knee model includes representation of the
menisci. Two simulations demonstrating the method are presented. The first simulation
uses data provided by the “Grand Challenge Competition to Predict In-Vivo Knee
Loads” [1] and simulates a dual limb squat from a subject with an instrumented total
knee prosthetic. The second simulation also simulates a squat and embeds a previously
validated cadaver based knee model within a musculoskeletal model of a subject of
similar height and weight as the cadaver donor. Predicted tibio-femoral loading and
ground reaction forces are compared to measured values for the subject with prosthetic
knee. Loading on the tibia plateau for squat simulations with intact and deficient
anterior cruciate ligament are presented for the subject with natural knee.
2. INTRODUCTION
Knowledge of knee loading would benefit prosthetic design, development of tissue
engineered materials, orthopedic repair, and management of degenerative joint diseases
such as osteoarthritis. Musculoskeletal modeling provides a method for estimating in
vivo joint loading during movement. The inverse dynamics method can predict net joint
forces and moments using measured ground reaction forces, motion, and
anthropometrics. Optimization methods can then be used to predict muscle forces that
reproduce the net loads at a joint and that meet an optimization objective such as
minimization of muscle force. The forward dynamics method calculates muscle forces
that reproduce predicted joint motions and torques based on inverse dynamics solutions.
For example, forward dynamics simulations may use an optimization method requiring
many iterative simulations to find muscle activation patterns that minimize differences
between experimental and predicted movement [2].
Musculoskeletal modeling of movement typically involves simplifications of the
joints, for example, the knee is often represented as a simple hinge joint. These
simplifications affect joint motion, muscle force prediction, and estimates of joint
loading. Presented here are two examples of muscle driven forward dynamics
movement simulations that include anatomical knee models developed in the multibody
framework. Both simulations include subjects performing a dual limb squat. The
1 Associate Professor, Mechanical Engineering, University of Missouri – Kansas City, Kansas City, MO,
USA