The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
CEINMS: A toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks
Open accessAbstract
Personalized neuromusculoskeletal (NMS) models can represent the neurological, physiological, and anatomical characteristics of an individual and can be used to estimate the forces generated inside the human body. Currently, publicly available software to calculate muscle forces are restricted to static and dynamic optimisation methods, or limited to isometric tasks only. We have created and made freely available for the research community the Calibrated EMG-Informed NMS Modelling Toolbox (CEINMS), an OpenSim plug-in that enables investigators to predict different neural control solutions for the same musculoskeletal geometry and measured movements. CEINMS comprises EMG-driven and EMG-informed algorithms that have been previously published and tested. It operates on dynamic skeletal models possessing any number of degrees of freedom and musculotendon units and can be calibrated to the individual to predict measured joint moments and EMG patterns. In this paper we describe the components of CEINMS and its integration with OpenSim. We then analyse how EMG-driven, EMG-assisted, and static optimisation neural control solutions affect the estimated joint moments, muscle forces, and muscle excitations, including muscle co-contraction.
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Cites
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OpenSim: Open-Source Software to Create and Analyze Dynamic Simulations of Movement
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An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo
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Self-citationDynamic Optimization of Human Walking
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Cited by
Techniques to determine knee joint contact forces during squatting: A systematic review
Kothurkar, R., & Lekurwale, R. (2022) · Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine · doi:10.1177/09544119221091609 · Cited by 9
Metadata
- Authors
- Pizzolato, C., Lloyd, D. G., Sartori, M., Ceseracciu, E., Besier, T. F., Fregly, B. J., & Reggiani, M.
- Venue
- Journal of Biomechanics
- Publisher
- Elsevier BV
- Published
- 2015-11
- Volume
- 48
- Issue
- 14
- Pages
- 3929-3936
- ISSN
- 0021-9290 (ISSN-L)
- OpenAlex
- W1755608697
- Cited by
- 349
- References
- 36
- FWCI
- 7.71
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Pizzolato, C., Lloyd, D. G., Sartori, M., Ceseracciu, E., Besier, T. F., Fregly, B. J., & Reggiani, M. (2015). CEINMS: A toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks. Journal of Biomechanics. https://doi.org/10.1016/j.jbiomech.2015.09.021
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