You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation
|
|---|---|
| Published in |
Source Code for Biology and Medicine, November 2015
|
| DOI | 10.1186/s13029-015-0044-4 |
| Pubmed ID | |
| Authors |
Alice Mantoan, Claudio Pizzolato, Massimo Sartori, Zimi Sawacha, Claudio Cobelli, Monica Reggiani |
| Abstract |
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. 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. 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. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 177 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 1% |
| United Kingdom | 1 | <1% |
| Spain | 1 | <1% |
| Germany | 1 | <1% |
| Unknown | 172 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 43 | 24% |
| Researcher | 26 | 15% |
| Student > Master | 26 | 15% |
| Student > Bachelor | 16 | 9% |
| Student > Doctoral Student | 9 | 5% |
| Other | 32 | 18% |
| Unknown | 25 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 86 | 49% |
| Computer Science | 10 | 6% |
| Sports and Recreations | 9 | 5% |
| Medicine and Dentistry | 8 | 5% |
| Nursing and Health Professions | 6 | 3% |
| Other | 19 | 11% |
| Unknown | 39 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 September 2021.
All research outputs
#4,132,705
of 22,833,393 outputs
Outputs from Source Code for Biology and Medicine
#23
of 127 outputs
Outputs of similar age
#50,584
of 252,470 outputs
Outputs of similar age from Source Code for Biology and Medicine
#1
of 6 outputs
Altmetric has tracked 22,833,393 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 127 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 81% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 252,470 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them