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Neuro-musculoskeletal simulation of instrumented contracture and spasticity assessment in children with cerebral palsy

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, July 2016
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Title
Neuro-musculoskeletal simulation of instrumented contracture and spasticity assessment in children with cerebral palsy
Published in
Journal of NeuroEngineering and Rehabilitation, July 2016
DOI 10.1186/s12984-016-0170-5
Pubmed ID
Authors

Marjolein Margaretha van der Krogt, Lynn Bar-On, Thalia Kindt, Kaat Desloovere, Jaap Harlaar

Abstract

Increased resistance in muscles and joints is an important phenomenon in patients with cerebral palsy (CP), and is caused by a combination of neural (e.g. spasticity) and non-neural (e.g. contracture) components. The aim of this study was to simulate instrumented, clinical assessment of the hamstring muscles in CP using a conceptual model of contracture and spasticity, and to determine to what extent contracture can be explained by altered passive muscle stiffness, and spasticity by (purely) velocity-dependent stretch reflex. Instrumented hamstrings spasticity assessment was performed on 11 children with CP and 9 typically developing children. In this test, the knee was passively stretched at slow and fast speed, and knee angle, applied forces and EMG were measured. A dedicated OpenSim model was created with motion and muscles around the knee only. Contracture was modeled by optimizing the passive muscle stiffness parameters of vasti and hamstrings, based on slow stretch data. Spasticity was modeled using a velocity-dependent feedback controller, with threshold values derived from experimental data and gain values optimized for individual subjects. Forward dynamic simulations were performed to predict muscle behavior during slow and fast passive stretches. Both slow and fast stretch data could be successfully simulated by including subject-specific levels of contracture and, for CP fast stretches, spasticity. The RMS errors of predicted knee motion in CP were 1.1 ± 0.9° for slow and 5.9 ± 2.1° for fast stretches. CP hamstrings were found to be stiffer compared with TD, and both hamstrings and vasti were more compliant than the original generic model, except for the CP hamstrings. The purely velocity-dependent spasticity model could predict response during fast passive stretch in terms of predicted knee angle, muscle activity, and fiber length and velocity. Only sustained muscle activity, independent of velocity, was not predicted by our model. The presented individually tunable, conceptual model for contracture and spasticity could explain most of the hamstring muscle behavior during slow and fast passive stretch. Future research should attempt to apply the model to study the effects of spasticity and contracture during dynamic tasks such as gait.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 230 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 1%
Sweden 1 <1%
Switzerland 1 <1%
India 1 <1%
United States 1 <1%
Unknown 223 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 54 23%
Student > Master 34 15%
Researcher 29 13%
Student > Bachelor 23 10%
Student > Doctoral Student 10 4%
Other 29 13%
Unknown 51 22%
Readers by discipline Count As %
Engineering 75 33%
Medicine and Dentistry 22 10%
Nursing and Health Professions 20 9%
Neuroscience 9 4%
Sports and Recreations 7 3%
Other 26 11%
Unknown 71 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 March 2018.
All research outputs
#16,721,208
of 25,371,288 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#885
of 1,413 outputs
Outputs of similar age
#234,007
of 372,889 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#14
of 19 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,413 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 372,889 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.