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MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation
BACKGROUND: Neuromusculoskeletal modeling and simulation enable investigation of the neuromusculoskeletal system and its role in human movement dynamics. These methods are progressively introduced into daily clinical practice. However, a major factor limiting this translation is the lack of robust t...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4647340/ https://www.ncbi.nlm.nih.gov/pubmed/26579208 http://dx.doi.org/10.1186/s13029-015-0044-4 |
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author | Mantoan, Alice Pizzolato, Claudio Sartori, Massimo Sawacha, Zimi Cobelli, Claudio Reggiani, Monica |
author_facet | Mantoan, Alice Pizzolato, Claudio Sartori, Massimo Sawacha, Zimi Cobelli, Claudio Reggiani, Monica |
author_sort | Mantoan, Alice |
collection | PubMed |
description | BACKGROUND: Neuromusculoskeletal modeling and simulation enable investigation of the neuromusculoskeletal system and its role in human movement dynamics. These methods are progressively introduced into daily clinical practice. However, a major factor limiting this translation is the lack of robust tools for the pre-processing of experimental movement data for their use in neuromusculoskeletal modeling software. RESULTS: This paper presents MOtoNMS (matlab MOtion data elaboration TOolbox for NeuroMusculoSkeletal applications), a toolbox freely available to the community, that aims to fill this lack. MOtoNMS processes experimental data from different motion analysis devices and generates input data for neuromusculoskeletal modeling and simulation software, such as OpenSim and CEINMS (Calibrated EMG-Informed NMS Modelling Toolbox). MOtoNMS implements commonly required processing steps and its generic architecture simplifies the integration of new user-defined processing components. MOtoNMS allows users to setup their laboratory configurations and processing procedures through user-friendly graphical interfaces, without requiring advanced computer skills. Finally, configuration choices can be stored enabling the full reproduction of the processing steps. MOtoNMS is released under GNU General Public License and it is available at the SimTK website and from the GitHub repository. Motion data collected at four institutions demonstrate that, despite differences in laboratory instrumentation and procedures, MOtoNMS succeeds in processing data and producing consistent inputs for OpenSim and CEINMS. CONCLUSIONS: MOtoNMS fills the gap between motion analysis and neuromusculoskeletal modeling and simulation. Its support to several devices, a complete implementation of the pre-processing procedures, its simple extensibility, the available user interfaces, and its free availability can boost the translation of neuromusculoskeletal methods in daily and clinical practice. |
format | Online Article Text |
id | pubmed-4647340 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46473402015-11-18 MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation Mantoan, Alice Pizzolato, Claudio Sartori, Massimo Sawacha, Zimi Cobelli, Claudio Reggiani, Monica Source Code Biol Med Methodology BACKGROUND: Neuromusculoskeletal modeling and simulation enable investigation of the neuromusculoskeletal system and its role in human movement dynamics. These methods are progressively introduced into daily clinical practice. However, a major factor limiting this translation is the lack of robust tools for the pre-processing of experimental movement data for their use in neuromusculoskeletal modeling software. RESULTS: This paper presents MOtoNMS (matlab MOtion data elaboration TOolbox for NeuroMusculoSkeletal applications), a toolbox freely available to the community, that aims to fill this lack. MOtoNMS processes experimental data from different motion analysis devices and generates input data for neuromusculoskeletal modeling and simulation software, such as OpenSim and CEINMS (Calibrated EMG-Informed NMS Modelling Toolbox). MOtoNMS implements commonly required processing steps and its generic architecture simplifies the integration of new user-defined processing components. MOtoNMS allows users to setup their laboratory configurations and processing procedures through user-friendly graphical interfaces, without requiring advanced computer skills. Finally, configuration choices can be stored enabling the full reproduction of the processing steps. MOtoNMS is released under GNU General Public License and it is available at the SimTK website and from the GitHub repository. Motion data collected at four institutions demonstrate that, despite differences in laboratory instrumentation and procedures, MOtoNMS succeeds in processing data and producing consistent inputs for OpenSim and CEINMS. CONCLUSIONS: MOtoNMS fills the gap between motion analysis and neuromusculoskeletal modeling and simulation. Its support to several devices, a complete implementation of the pre-processing procedures, its simple extensibility, the available user interfaces, and its free availability can boost the translation of neuromusculoskeletal methods in daily and clinical practice. BioMed Central 2015-11-16 /pmc/articles/PMC4647340/ /pubmed/26579208 http://dx.doi.org/10.1186/s13029-015-0044-4 Text en © Mantoan et al. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Mantoan, Alice Pizzolato, Claudio Sartori, Massimo Sawacha, Zimi Cobelli, Claudio Reggiani, Monica MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation |
title | MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation |
title_full | MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation |
title_fullStr | MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation |
title_full_unstemmed | MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation |
title_short | MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation |
title_sort | motonms: a matlab toolbox to process motion data for neuromusculoskeletal modeling and simulation |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4647340/ https://www.ncbi.nlm.nih.gov/pubmed/26579208 http://dx.doi.org/10.1186/s13029-015-0044-4 |
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