Abstract
Background
Musculoskeletal simulations are used to estimate muscle-tendon and joint contact forces (JCF). Personalizing the model's femoral geometry has been shown to improve the accuracy of JCF calculations. It is, however, unknown if the personalized geometry improves the agreement between estimated muscle activations and experimentally measured electromyography (EMG) signals.Research question
Does personalizing the musculoskeletal geometry improve the agreement between estimated muscle activations and EMG signals in terms of timing?Methods
We retrospectively analysed data from Bosmans et al. [5], which included three-dimensional motion capture data, EMG signals of eight lower limb muscles on each leg, and magnetic resonance imaging (MRI) data from seven children with cerebral palsy. For each patient we created a generic-scaled model and MRI-based model, which accounted for the subject-specific musculoskeletal geometry. We calculated muscle activations, muscle-tendon forces and JCF. Muscle activations were compared to the EMG signals using coefficient of determination and cosines similarity.Results
MRI-based models altered the magnitude of muscle activations and had a large impact on JCF but did not change the muscle activations profiles and therefore did not improve the agreement with EMG signals.Significance
MRI-based models do not alter the shape of muscle activations. Hence, if detailed muscle activations are a desired output of the simulations, EMG-informed modeling approaches should be used for musculoskeletal simulation in children with cerebral palsy. Furthermore, our study highlighted that altered JCF does not necessarily mean accurate muscle activations. To improve patient-specific simulations, future work should focus on developing methods to estimate cost functions representative for the neural control of children with cerebral palsy.