Characteristics associated with improved knee extension after strength training for individuals with cerebral palsy and crouch gait

Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA.
Journal of pediatric rehabilitation medicine 06/2012; 5(2):99-106. DOI: 10.3233/PRM-2012-0201
Source: PubMed


Muscle weakness may contribute to crouch gait in individuals with cerebral palsy, and some individuals participate in strength training programs to improve crouch gait. Unfortunately, improvements in muscle strength and gait are inconsistent after completing strength training programs. The purpose of this study was to examine changes in knee extensor strength and knee extension angle during walking after strength training in individuals with cerebral palsy who walk in crouch gait and to determine subject characteristics associated with these changes. A literature review was performed of studies published since January 2000 that included strength training, three-dimensional motion analysis, and knee extensor strength measurements for individuals with cerebral palsy. Three studies met these criteria and individual subject data was obtained from the authors for thirty crouch gait subjects. Univariate regression analyses were performed to determine which of ten physical examination and motor performance variables were associated with changes in strength and knee extension during gait. Change in knee extensor strength ranged from a 25% decrease to a 215% increase, and change in minimum knee flexion angle during gait ranged from an improvement of 9° more knee extension to 15° more knee flexion. Individuals without hamstring spasticity had greater improvement in knee extension after strength training. Hamstring spasticity was associated with an undesired increase in knee flexion during walking. Subject-specific factors such as hamstring spasticity may be useful for predicting which subjects will benefit from strength training to improve crouch gait.

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Available from: Marianne Unger, Jun 17, 2015
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    • "In this new context, subject-specific models, typically generated from heterogeneous data such as clinical images, published atlases and direct anthropometrical measurements , are key factors in the calculation of reliable mechanical variables (Lenaerts et al. 2008, 2009; Scheys et al. 2008; Valente et al. 2012). For example, subjectspecific models were found to be key factors for an accurate calculation of muscle lever arms (Lenaerts et al. 2008; Valente et al. 2012), skeletal forces (Lenaerts et al. 2008), bone stresses (Jonkers et al. 2008) and for properly addressing the related clinical implications (Steele et al. 2012; Taddei et al. 2012). However, the error committed in extracting the model parameters from the available clinical information affects the calculated variables in a way that needs to be investigated. "
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    ABSTRACT: Subject-specific musculoskeletal models have become key tools in the clinical decision-making process. However, the sensitivity of the calculated solution to the unavoidable errors committed while deriving the model parameters from the available information is not fully understood. The aim of this study was to calculate the sensitivity of all the kinematics and kinetics variables to the inter-examiner uncertainty in the identification of the lower limb joint models. The study was based on the computer tomography of the entire lower-limb from a single donor and the motion capture from a body-matched volunteer. The hip, the knee and the ankle joint models were defined following the International Society of Biomechanics recommendations. Using a software interface, five expert anatomists identified on the donor's images the necessary bony locations five times with a three-day time interval. A detailed subject-specific musculoskeletal model was taken from an earlier study, and re-formulated to define the joint axes by inputting the necessary bony locations. Gait simulations were run using OpenSim within a Monte Carlo stochastic scheme, where the locations of the bony landmarks were varied randomly according to the estimated distributions. Trends for the joint angles, moments, and the muscle and joint forces did not substantially change after parameter perturbations. The highest variations were as follows: (a) 11° calculated for the hip rotation angle, (b) 1% BW × H calculated for the knee moment and (c) 0.33 BW calculated for the ankle plantarflexor muscles and the ankle joint forces. In conclusion, the identification of the joint axes from clinical images is a robust procedure for human movement modelling and simulation.
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