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MOtoNMS v2.2

Authors: Alice Mantoan; Monica Reggiani;
Abstract

Matlab MOtion data elaboration TOolbox for NeuroMusculoSkeletal applications (MOtoNMS) is a freely available Matlab toolbox that aims at providing a complete tool for processing movement data for their use in neuromusculoskeletal software. It is able to read motion data stored in C3D files and process marker trajectories, ground reaction forces, and EMG signals for the OpenSim and CEINMS software. MOtoNMS has been design to be flexible and highly configurable: users can easily setup their own laboratory and processing procedures, without constraints in instruments, software, protocols, and methodologies. At the same time it is also quite simple to use thanks to its graphical user-friendly interfaces that help users in configuring the process without any change in Matlab code. MOtoNMS also improves the data organization, providing a clear structure of input data and automatically generating output directories. Release 2.2 has been updated to support two largely required features: trials with different directions of motion force plates with pads MOtoNMS 2.2 also provides the users with additional logging information about the EMG processing steps. An new output folder (maxemg) is created for each dynamic elaboration, with plots and log data related to the computation of maximum EMG values. A last objective of this release is improving the processing of marker trajectories. Users have the possibility to define the gaps' maximum size that will be interpolated, and a piecewise filtering has been implemented for markers trajectories that still have NaN values. Finally, computation of joint centers in Static Elaboration is no more mandatory.

Related Organizations
Keywords

Neuromusculoskeletal Modeling and Simulation, OpenSim, Motion Data Processing

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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