Development of a simulation platform to study the role of joint hyper-resistance in functional tasks in children with cerebral palsy.

Informations projet

simSpas

N° de convention de subvention: 101068850

DOI

10.3030/101068850

Projet clôturé

Date de signature de la CE 16 Septembre 2022

Date de début 1 Octobre 2022

Date de fin 30 Septembre 2024

Financé au titre de

• Marie Skłodowska-Curie Actions (MSCA)

Coût total

Aucune donnée

Contribution de l’UE

€ 191 760,00

Coordonné par

KATHOLIEKE UNIVERSITEIT LEUVEN
Belgium

Periodic Reporting for period 1 - simSpas (Development of a simulation platform to study the role of joint hyper-resistance in functional tasks in children with cerebral palsy.)

Période du rapport: 2022-10-01 au 2024-09-30

Résumé du contexte et des objectifs généraux du projet

In this project, we developed simulation methods that can be used to help understand the underlying mechanics of movement disorders in children with cerebral palsy, and to aid treatment planning. Children with cerebral palsy suffer from multiple neuro-musculoskeletal deficits like decreased muscle selectivity, increased spinal reflex, increased muscle tone and skeletal deformities that cause gait deficits. Moreover, there is a big diversity in the presence and intensity of each deficit in different affected children, making it hard to study the underlying mechanics of individual deficits only using experiments. Indeed, the success rates of surgeries in children with cerebral palsy have not improved in the last 15 years. Recently developed state-of-the-art musculoskeletal modelling and simulations can help us understand the role of individual deficits and their interaction on gait deficits as we can develop physics-based models of each deficit and study their effect on movement in isolation and in presence of specific deficits. The same simulations can then be used to study the effect of addressing deficits in isolation and/or in combination to aid treatment planning. In this project, we improved the accuracy of the musculoskeletal model personalization that will improve the accuracy what we learn from musculoskeletal modelling and simulation studies and the accuracy of proposed treatment planning. Additionally, this project contributed towards making the state-of-the-art musculoskeletal modelling and simulations platform easy to use. An open source software called PredSim was created that can be used not only for studying children with cerebral palsy, but also human gait and running, disorders like stroke, Duchenne muscular dystrophy, walking with prosthesis, and even animal and bird locomotion.

Additionally, in this project, we also developed tools to study certain underlying mechanics in children with cerebral palsy that cannot be studied using PredSim. Sensory signals and motor commands are corrupted by errors called sensorimotor noise. A heightened gastrocnemius activity at heel-strike has been observed in children with cerebral palsy, and it has been theorized that the reason for this high gastrocnemius activity could be the presence of high sensorimotor noise and/or the interaction of sensorimotor noise with other deficits in children with cerebral palsy. Since PredSim does not account for sensorimotor noise, it is not able to predict the observed heightened gastrocnemius activity. Accounting for sensorimotor noise along with a complex control policy in simulations is computationally very expensive, and for that reason, most simulation generating platforms do not account for it. This limitation was recently addressed by prof. dr. Friedl De Groote. They developed a simulation platform that could generate simulations of walking while accounting for sensorimotor noise. This platform, however, used a simple stick figure human model without any feet or muscles. To study the role of sensorimotor noise, and its interaction with other deficits during gastrocnemius activity at heel-strike, the fellowship recipient added feet and muscles to the simulation platform that accounts for sensorimotor noise. These developments will enable researchers to study isolated an interaction effects of sensorimotor noise in children with cerebral palsy.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

To study the underlying mechanics of cerebral palsy and propose treatment plans, we use predictive simulations that employ physics-based simulations developed by prof. dr. Friedl De Groote to predict the movement patterns of a human model that encodes the underlying control and musculoskeletal deficits. In this project, the fellowship recipient worked as a part of a team to make predictive simulations easy to use. A tool called PredSim was developed and is free to download from github.

The PredSim platform can be used to study the effect of addressing deficits in isolation and/or in combination to aid treatment planning. The first step in this process is to accurately represent the altered muscle-tendon properties of the children in the simulation environment. For this purpose, experimental data is collected, and an optimization routine is run to estimate the muscle-tendon properties that would satisfy the electromyography – joint moment relationship obtained experimentally. This method, however, had limitations as the number of properties that can be accurately estimated depends on the richness of the experimental data. For example, properties of muscle with primary action in the frontal plane cannot be reliably determined if all the collected experimental data was of movements that are primarily in the sagittal plane. In this project, the fellowship recipient used principles of system identification to determine which muscle-tendon properties can be reliably estimated from a given dataset.

To study the role of sensorimotor noise in heightened gastrocnemius activity at heel-strike has been observed in children with cerebral palsy, the fellowship recipient added feet and muscles to the stick figure model previously used to generate simulations that account for sensorimotor noise.

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

The PredSim tool is already being used by researchers around the globe to study human gait and running, disorders like stroke, Duchenne muscular dystrophy, cerebral palsy, walking with prosthesis, and even animal and bird locomotion. We organized a workshop to teach researcher how to use the PredSim tool. The workshop was attended b y43 researchers from 13 nations.

The musculoskeletal model personalization was changed such that only the muscle-tendon parameters that are reliably identifiable from a given dataset are estimated. It was determined that estimating only the identifiable muscle-tendon parameters, rather than all the parameters, did not change the movement patterns of the simulation. This result improves the quality of simulations since all the estimated muscle-tendon properties are reliable, without reducing the quality of simulation. Additionally, this step is crucial to ensure that the accuracy of the treatment plan using simulations.

The new platform that accounts for sensorimotor noise during gait while following a complex control policy was able to better predict key movement characteristics like the knee flexion angle during swing, and the predicted variability in movement was in experimental range and followed the general shape of the experimental data. This platform is a major leap forward in understanding the role of sensorimotor noise and its interaction with other deficits in children with cerebral palsy. Additionally, the platform can be used for other movement disorders.