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Session: Poster session II
Session starts: Thursday 24 January, 16:00

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Kirsten Veerkamp ()
Thomas Geijtenbeek ()
Jaap Harlaar ()
Marjolein van der Krogt ()

Abstract:
Children with cerebral palsy (CP) often show problems with gait due to both neural and non-neural impairments [1]. Optimal treatment selection is challenging because of the complex, multilevel nature of these problems. Neuro-musculoskeletal modelling might provide a valuable source of information to assist in treatment selection, by having potential to predict post-treatment outcomes. However, often generic models are used, which are based on healthy adults and therefore their use may not be accurate in a clinical population like CP. Hence, an essential step forward is to implement patient-specific features into the model. The aim of this project is to develop and validate predictive gait simulations incorporating various impairments as present in CP. Recently, a platform for forward dynamic, predictive gait simulations has been developed (SCONE https://simtk.org/projects/scone). This platform implements a two-dimensional OpenSim [2] model with realistic Hill-type muscles and includes various customizable control strategies, allowing to create a stable and realistic gait pattern. The kinematics (joint angles), kinetics (ground reaction forces, joint moments and joint powers) and muscle activation patterns predicted by the forward dynamic simulations of the model will be compared to experimental gait data. Various impairments that are common in CP (i.e. muscle weakness, spasticity and joint contracture) will be implemented into the model separately. Experimental gait data of people with ankle plantar flexor weakness, ankle spasticity and with increased ankle joint stiffness imposed by kinesiotape will be used for validation, respectively. Finally, all three of these impairments will be combined in the model and compared to gait data of patients showing varying levels of weakness, spasticity and contracture. Statistical parametric mapping will be used to compare the model predictions and experimental data. This project will provide fundamental insights into the effects of various common impairments in CP on gait performance. This knowledge can be valuable for understanding the underlying pathologies. In addition, the development of patient-specific predictive simulations may be an important step forwards to using neuro-musculoskeletal modelling as a predictive tool in clinical practice, with the ultimate goal of improving the challenging treatment selection in patients with complex neurological disorders. References [1] Graham et al., Nature Reviews Disease Primers (2016) [2] Delp et al., IEEE Transactions on Biomedical Engineering (2007)