Using Dynamic in vivo Kinematics for Subject-Specific Calibration of Knee Ligament Parameters
Authors: Nelson Stephen 
Published: April 2022

In vivo clinical studies are the optimal way to investigate the biomechanical outcomes of new prosthetic devices.
This particular style of testing can be difficult and, in certain cases, unethical to perform. The testing of unproven
devices, surgical techniques, and materials put patients at risk from unanticipated outcomes in how these devices respond
to the in vivo environment and patient-specific loading conditions. Biomechanical computational models were developed to
provide validation to new devices prior to clinical testing. Computational models for use in optimizing knee prosthetics
frequently include ligament representations, but these representations have inherent uncertainty due to wide intersubject
variation across the population and difficulties in defining the subject-specific properties of the ligament. Typically,
these parameters are tuned using a trial-and-error approach by experienced personnel or by adapting literature values.
However, published values for ligament constants have been shown to vary greatly. Due to these issues, previous studies
have recommended the use of a sensitivity analysis to validate input parameters and incorporate uncertainty into finite
element (FE) analyses. FE simulations have been widely used in implant development, but this has largely been performed
using subjects with a normal body mass index (BMI). Increasing BMI has been shown to negatively impact the outcomes of
total knee arthroplasty (TKA) procedures. Better understanding of obesity’s impact on joint kinematics will help with
design refinement for prosthetics used in obese individuals.

The first objective of this study was to use dynamic, in vivo kinematics to bound subject-specific ligament parameters
to a region that will produce physiological forces, thus removing some uncertainty associated with ligament properties.
A Monte Carlo simulation was used to find the region of physiological properties for each subject across multiple dynamic
activities. The resulting, subject-specific regions were then compared between cohorts of high BMI and normal BMI subjects.
Significant differences were found between the bounding areas for these groups. Additionally, there were ligaments that had
significant differences when age and gender were considered. This study indicates that there are likely cohort-specific differences in in vivo ligament properties.

The secondary objective was to create a model database of three high BMI subjects as they perform five activities of
daily living. Subject-specific, FE simulations were created for the three subjects using kinematics that were derived
from experimental data of the subjects completing various exercises. Controllers were developed and tuned to apply the
muscle forces, matching profiles generated from the kinematic data. The models correctly reflect the target profiles
and are a crucial first step to analyze the outcomes of prosthetic devices in the obese population. Industry partners
are currently using this model database to virtually implant prosthetic devices and measure how the resulting kinematics match the natural, non-implanted knee.