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Effective force control by muscle synergies

Overview of attention for article published in Frontiers in Computational Neuroscience, April 2014
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Title
Effective force control by muscle synergies
Published in
Frontiers in Computational Neuroscience, April 2014
DOI 10.3389/fncom.2014.00046
Pubmed ID
Authors

Denise J. Berger, Andrea d'Avella

Abstract

Muscle synergies have been proposed as a way for the central nervous system (CNS) to simplify the generation of motor commands and they have been shown to explain a large fraction of the variation in the muscle patterns across a variety of conditions. However, whether human subjects are able to control forces and movements effectively with a small set of synergies has not been tested directly. Here we show that muscle synergies can be used to generate target forces in multiple directions with the same accuracy achieved using individual muscles. We recorded electromyographic (EMG) activity from 13 arm muscles and isometric hand forces during a force reaching task in a virtual environment. From these data we estimated the force associated to each muscle by linear regression and we identified muscle synergies by non-negative matrix factorization. We compared trajectories of a virtual mass displaced by the force estimated using the entire set of recorded EMGs to trajectories obtained using 4-5 muscle synergies. While trajectories were similar, when feedback was provided according to force estimated from recorded EMGs (EMG-control) on average trajectories generated with the synergies were less accurate. However, when feedback was provided according to recorded force (force-control) we did not find significant differences in initial angle error and endpoint error. We then tested whether synergies could be used as effectively as individual muscles to control cursor movement in the force reaching task by providing feedback according to force estimated from the projection of the recorded EMGs into synergy space (synergy-control). Human subjects were able to perform the task immediately after switching from force-control to EMG-control and synergy-control and we found no differences between initial movement direction errors and endpoint errors in all control modes. These results indicate that muscle synergies provide an effective strategy for motor coordination.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 203 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 <1%
Netherlands 1 <1%
Austria 1 <1%
Brazil 1 <1%
Canada 1 <1%
Spain 1 <1%
United States 1 <1%
Poland 1 <1%
Unknown 194 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 52 26%
Student > Master 31 15%
Researcher 29 14%
Student > Doctoral Student 22 11%
Other 7 3%
Other 25 12%
Unknown 37 18%
Readers by discipline Count As %
Engineering 88 43%
Neuroscience 21 10%
Sports and Recreations 14 7%
Agricultural and Biological Sciences 11 5%
Computer Science 10 5%
Other 17 8%
Unknown 42 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 15 May 2014.
All research outputs
#17,720,553
of 22,755,127 outputs
Outputs from Frontiers in Computational Neuroscience
#957
of 1,338 outputs
Outputs of similar age
#155,809
of 226,133 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#16
of 20 outputs
Altmetric has tracked 22,755,127 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,338 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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 226,133 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.