Multiscale musculoskeletal modelling, data - model fusion and electromyography-informed modelling
2016 | journal article. A publication with affiliation to the University of Göttingen.
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Multiscale musculoskeletal modelling, data - model fusion and electromyography-informed modelling
Fernandez, J.; Zhang, J.; Heidlauf, T.; Sartori, M. ; Besier, T. F.; Roehrle, O. & Lloyd, D. G. (2016)
Interface Focus, 6(2) art. 20150084. DOI: https://doi.org/10.1098/rsfs.2015.0084
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Details
- Authors
- Fernandez, J.; Zhang, J.; Heidlauf, T.; Sartori, Massimo ; Besier, Thor F.; Roehrle, O.; Lloyd, David G.
- Abstract
- This paper proposes methods and technologies that advance the state of the art for modelling the musculoskeletal system across the spatial and temporal scales; and storing these using efficient ontologies and tools. We present population-based modelling as an efficient method to rapidly generate individual morphology from only a few measurements and to learn from the ever-increasing supply of imaging data available. We present multiscale methods for continuum muscle and bone models; and efficient mechanostatistical methods, both continuum and particle-based, to bridge the scales. Finally, we examine both the importance that muscles play in bone remodelling stimuli and the latest muscle force prediction methods that use electromyography-assisted modelling techniques to compute musculoskeletal forces that best reflect the underlying neuromuscular activity. Our proposal is that, in order to have a clinically relevant virtual physiological human, (i) bone and muscle mechanics must be considered together; (ii) models should be trained on population data to permit rapid generation and use underlying principal modes that describe both muscle patterns and morphology; and (iii) these tools need to be available in an open-source repository so that the scientific community may use, personalize and contribute to the database of models.
- Issue Date
- 2016
- Status
- published
- Publisher
- Royal Soc
- Journal
- Interface Focus
- ISSN
- 2042-8901; 2042-8898