Neuromuscular characterisation in Cerebral Palsy using hybrid Hill-type models on isometric contractions

Integration of neural architecture within a finite element framework for improved neuromusculoskeletal modeling

Neuromusculoskeletal (NMS) models can aid in studying the impacts of the nervous and musculoskeletal systems on one another. These computational models facilitate studies investigating mechanisms and treatment of musculoskeletal and neurodegenerative conditions. In this study, we present a predictive NMS model that uses an embedded neural architecture within a finite element (FE) framework to simulate muscle activation. A previously developed neuromuscular model of a motor neuron was embedded into a simple FE musculoskeletal model. Input stimulation profiles from literature were simulated in the FE NMS model to verify effective integration of the software platforms. Motor unit recruitment and rate coding capabilities of the model were evaluated. The integrated model reproduced previously published output muscle forces with an average error of 0.0435 N. The integrated model effectively demonstrated motor unit recruitment and rate coding in the physiological range based upon motor unit discharge rates and muscle force output. The combined capability of a predictive NMS model within a FE framework can aid in improving our understanding of how the nervous and musculoskeletal systems work together. While this study focused on a simple FE application, the framework presented here easily accommodates increased complexity in the neuromuscular model, the FE simulation, or both.

A New Muscle Activation Dynamics Model, That Simulates the Calcium Kinetics and Incorporates the Role of Store-Operated Calcium Entry Channels, to Enhance the EMG-Driven Hill-type Models

Hill-type models are frequently used in biomechanical simulations. They are attractive for their low computational cost and close relation to commonly measured musculotendon parameters. Still, more attention is needed to improve the activation dynamics of the model specifically because of the nonlinearity observed in the EMG-Force relation. Moreover, one of the important and practical questions regarding the assessment of the model's performance is how adequately can the model simulate any fundamental type of human movement without modifying model parameters for different tasks? This paper tries to answer this question by proposing a simple physiologically based activation dynamics model. The model describes the ?kinetics of the calcium dynamics while activating and deactivating the muscle contraction process. Hence, it allowed simulating the recently discovered role of store-operated calcium entry (SOCE) channels as immediate counter-flux to calcium loss across the tubular system during excitation-contraction coupling. By comparing the ability to fit experimental data without readjusting the parameters, the proposed model has proven to have more steady performance than phenomenologically based models through different submaximal isometric contraction levels. This model indicates that more physiological insights is key for improving Hill-type model performance.

High-density electromyographic data during isometric contractions of the ankle joint in children with cerebral palsy pre and post BoNT-A treatment

Understanding the underlying mechanisms leading to progressive muscle pathologies in spastic Cerebral Palsy remains a challenging field of research. Furthermore, Botulinum Neurotoxin-A (BoNT-A) is a frequent intervention to treat spasticity in CP but its effects on neuromuscular properties are not yet fully explored. High-density Electromyographic (HD-EMG) data have been collected before and after BoNT-A injections from children aged 5-15 years during isometric contractions of the ankle joint together with torque output, clinical assessments and demographic details. Data collected from a total of 13 children with and 29 children without spastic CP allow for between-group comparisons and are made available using Mendeley Data (https://doi.org/10.17632/3sbptrk54c.2 and https://doi.org/10.17632/3b98g5fyff.1).