MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation. Issue 1 (December 2015)

• Record Type: Journal Article
• Authors: Mantoan, Alice; Pizzolato, Claudio; Sartori, Massimo; Sawacha, Zimi; Cobelli, Claudio; Reggiani, Monica
• Is Part Of: Source code for biology and medicine. Volume 10:Issue 1(2015)
• Page Start: 1
• Page End: 14
• Publication Date: 2015-12
• Subjects: Neuromusculoskeletal modeling -- Motion data -- Data processing -- OpenSim -- C3D; Biology -- Data processing -- Periodicals; Medicine -- Data processing -- Periodicals; Bioinformatics -- Periodicals; 570.285
• DOI: 10.1186/s13029-015-0044-4
• Languages: English
• ISSNs: 1751-0473

Abstract

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.