Evaluation of Musculoskeletal Model Personalization for Gait Analysis of Children with Cerebral Palsy

Abstract

Musculoskeletal modeling and simulation has become a prominent tool in clinical gait analysis with the ability to provide insight into the underlying mechanisms of human movement. However, generic cadaver-based models have been shown to poorly reflect live subjects, especially those with pathologies such as cerebral palsy (CP). The main purpose of this thesis was to evaluate the effect of model personalization on gait simulation outcomes between models of varying level of personalization. Gait data from 7 children with CP was used for simulations in OpenSim using 3 different model types for each: scaled generic (GS), scaled generic with tibial torsion and femoral anteversion (TTAF), and MRI-based. MRI-based model outcomes saw the greatest differences from GS models in the hip and upper leg, specifically hamstrings and quadriceps, but also experienced moderate differences in the lower leg. Similar results were found when comparing MRI to TTAF models. TTAF models differed from the GS models around the subtalar joint, mainly the tibialis anterior. Larger differences in kinematics, kinetics, and muscle activations were accompanied by changes to the most influential model parameters, in descending order of importance, these were: tendon slack length, moment arm length, and normalized muscle fiber length. Despite the differences between these models, there was no indication that either is more accurate or more suitable for clinical use.