SimCP: A simulation platform to predict gait performance following orthopedic intervention in children with cerebral palsy
Biosystems and Biorobotics, ISSN: 2195-3570, Vol: 22, Page: 267-270
2019
- 27Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures27
- Readers27
- 27
Book Chapter Description
We present a simulation platform that will enable clinicians to evaluate the effect of different treatment options on gait performance in children with cerebral palsy (CP) in order to select the treatment with the highest potential to normalize the patient’s gait pattern. We present a case study to demonstrate the use of the platform. We created a neuro-musculoskeletal model of a 10-year old female child with mild spastic triplegic CP (GMFCS II) who was treated with single-event multilevel surgery based on medical imaging and motion capture data collected before the surgery. Based on this model, we predicted that the treatment would reduce the capability gap, i.e. the torque deficit of the patient with respect to the joint torques needed for normal walking. This prediction was in accordance with the closer-to-normal post-treatment gait kinetics of the child.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85055044213&origin=inward; http://dx.doi.org/10.1007/978-3-030-01887-0_51; http://link.springer.com/10.1007/978-3-030-01887-0_51; http://link.springer.com/content/pdf/10.1007/978-3-030-01887-0_51; https://dx.doi.org/10.1007/978-3-030-01887-0_51; https://link.springer.com/chapter/10.1007/978-3-030-01887-0_51
Springer Nature
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