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

Alice Mantoan; Claudio Pizzolato; Massimo Sartori; Zimi Sawacha; Claudio Cobelli; Monica Reggiani

doi:10.1186/s13029-015-0044-4

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

Source Code Biol Med. 2015 Nov 16:10:12. doi: 10.1186/s13029-015-0044-4. eCollection 2015.

Authors

Alice Mantoan¹, Claudio Pizzolato², Massimo Sartori³, Zimi Sawacha⁴, Claudio Cobelli⁴, Monica Reggiani¹

Affiliations

¹ Department of Management and Engineering, University of Padova, Stradella San Nicola, 3, Vicenza, 36100 Italy.
² Centre for Musculoskeletal Research, Griffith University, Gold Coast campus, Gold Coast QLD, 4222 Australia.
³ Department of Neurorehabilitation Engineering, University Medical Center Goettingen, Georg-August University, Von-Siebold-Str., 6, Goettingen, 37075 Germany.
⁴ Department of Information Engineering, University of Padova, Via Gradenigo, 6/b, Padova, 35131 Italy.

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.

Keywords: C3D; Data processing; Motion data; Neuromusculoskeletal modeling; OpenSim.