MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation.

Q2 Decision Sciences Source Code for Biology and Medicine Pub Date : 2015-11-16 eCollection Date: 2015-01-01 DOI:10.1186/s13029-015-0044-4
Alice Mantoan, Claudio Pizzolato, Massimo Sartori, Zimi Sawacha, Claudio Cobelli, Monica Reggiani
{"title":"MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation.","authors":"Alice Mantoan, Claudio Pizzolato, Massimo Sartori, Zimi Sawacha, Claudio Cobelli, Monica Reggiani","doi":"10.1186/s13029-015-0044-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":35052,"journal":{"name":"Source Code for Biology and Medicine","volume":"10 1","pages":"12"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4647340/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Source Code for Biology and Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s13029-015-0044-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2015/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"Decision Sciences","Score":null,"Total":0}
引用次数: 0

Abstract

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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
MOtoNMS:用于神经肌肉骨骼建模和仿真的运动数据处理 MATLAB 工具箱。
背景:通过神经肌肉骨骼建模和模拟,可以研究神经肌肉骨骼系统及其在人体运动动力学中的作用。这些方法正逐步被引入日常临床实践中。然而,限制这种转化的一个主要因素是缺乏用于神经肌肉骨骼建模软件的实验运动数据预处理的强大工具:本文介绍了 MOtoNMS(用于神经肌肉骨骼应用的 matlab 运动数据阐述工具箱),这是一个免费提供给社区使用的工具箱,旨在弥补这一不足。MOtoNMS 可处理来自不同运动分析设备的实验数据,并为 OpenSim 和 CEINMS(校准肌电图信息 NMS 建模工具箱)等神经肌肉骨骼建模和仿真软件生成输入数据。MOtoNMS 实现了常用的处理步骤,其通用架构简化了新的用户定义处理组件的集成。MOtoNMS 允许用户通过友好的图形界面设置实验室配置和处理程序,无需高级计算机技能。最后,还可以存储配置选择,以便全面复制处理步骤。MOtoNMS 根据 GNU 通用公共许可证发布,可在 SimTK 网站和 GitHub 存储库中获取。在四个机构收集的运动数据表明,尽管实验室仪器和程序存在差异,MOtoNMS 仍能成功处理数据,并为 OpenSim 和 CEINMS 生成一致的输入:MOtoNMS 填补了运动分析与神经肌肉骨骼建模和仿真之间的空白。其对多种设备的支持、预处理程序的完整实现、简单的可扩展性、可用的用户界面以及免费可用性,可促进神经肌肉骨骼方法在日常和临床实践中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Source Code for Biology and Medicine
Source Code for Biology and Medicine Decision Sciences-Information Systems and Management
自引率
0.00%
发文量
0
期刊介绍: Source Code for Biology and Medicine is a peer-reviewed open access, online journal that publishes articles on source code employed over a wide range of applications in biology and medicine. The journal"s aim is to publish source code for distribution and use in the public domain in order to advance biological and medical research. Through this dissemination, it may be possible to shorten the time required for solving certain computational problems for which there is limited source code availability or resources.
期刊最新文献
2DKD: a toolkit for content-based local image search. Computing and graphing probability values of pearson distributions: a SAS/IML macro. iPBAvizu: a PyMOL plugin for an efficient 3D protein structure superimposition approach Social support for collaboration and group awareness in life science research teams. MZPAQ: a FASTQ data compression tool.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1