Physics-Based Simulations to Predict the Differential Effects of Motor Control and Musculoskeletal Deficits on Gait Dysfunction in Cerebral Palsy: A Retrospective Case Study

Abstract

Physics-based simulations of walking have the theoretical potential to support clinical decision-making by predicting the functional outcome of treatments in terms of walking performance. Yet before using such simulations in clinical practice, their ability to identify the main treatment targets in specific patients needs to be demonstrated. In this study, we generated predictive simulations of walking with a medical imaging based neuro-musculoskeletal model of a child with cerebral palsy presenting crouch gait. We explored the influence of altered muscle-tendon properties, reduced neuromuscular control complexity, and spasticity on gait dysfunction in terms of joint kinematics, kinetics, muscle activity, and metabolic cost of transport. We modeled altered muscle-tendon properties by personalizing Hill-type muscle-tendon parameters based on data collected during functional movements, simpler neuromuscular control by reducing the number of independent muscle synergies, and spasticity through delayed muscle activity feedback from muscle force and force rate. Our simulations revealed that, in the presence of aberrant musculoskeletal geometries, altered muscle-tendon properties rather than reduced neuromuscular control complexity and spasticity were the primary cause of the crouch gait pattern observed for this child, which is in agreement with the clinical examination. These results suggest that muscle-tendon properties should be the primary target of interventions aiming to restore an upright gait pattern for this child. This suggestion is in line with the gait analysis following muscle-tendon property and bone deformity corrections. Future work should extend this single case analysis to more patients in order to validate the ability of our physics-based simulations to capture the gait patterns of individual patients pre-and post-treatment. Such validation would open the door for identifying targeted treatment strategies with the aim of designing optimized interventions for neuro-musculoskeletal disorders.

Evaluation of Synergy Extrapolation for Predicting Unmeasured Muscle Excitations from Measured Muscle Synergies

“…However, the synergy vector weights associated with "remaining" postures in Ajiboye and Weir (2009) or "excluded" muscles in Bianco et al (2018) were not predicted without knowledge of the muscle excitations being treated as unmeasured but rather were fitted with knowledge of those excitations using least square algorithms. Several other studies have imposed synergy structures on muscle excitations or activations through optimization when estimating knee contact force (Walter et al, 2014), joint stiffness (Shourijeh and Fregly, 2020), or motion (Clark et al, 2009;Allen and Neptune, 2012;Meyer et al, 2016;Mehrabi et al, 2019;Falisse et al, 2020). Imposing a muscle synergy structure on predicted muscle excitations or activations can not only eliminate discontinuities between neighboring time frames but also reduce the number of design variables in the optimization problem.…”

Clinical Relevance of State-of-the-Art Analysis of Surface Electromyography in Cerebral Palsy

“…The analysis of motor pool activation using multi-muscle sEMG can also be complemented by a statistical analysis of the muscle activity profiles and their decomposition into a small set of socalled muscle modules or common basic activation components (see the previous section) as a means to look backward from the periphery to the spinal cord motor programming and output (130,131). There are now several studies that evaluated the spinal locomotor output, its spatiotemporal organization and impairment in children with CP (37,100,(107)(108)(109)(110)(111)(112)(113)(114)(115)(116)(117)(118)(119)(120). Figure 3C illustrates the spinal maps of MN activation during walking and typical features of motor output impairment in children with CP compared to TD children obtained using the averaged rectified sEMG profiles of multiple leg muscles as an indirect measure of the net MN firing in the spinal cord.…”

Revealing the unique features of each individual’s muscle activation signatures

“…Multiple scientific domains are transitioning toward personalised approaches where diagnosis or treatment are based on individual characteristics (35). Such personalized approaches are crucial to improve our understanding of movement in healthy populations (36) as well as in populations with neurological disorders (37). Importantly, these approaches require the identification of an individual's unique features, but this is rarely performed for muscle activation.…”