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Evaluation of a Neuromechanical Walking Control Model Using Disturbance Experiments

Overview of attention for article published in Frontiers in Computational Neuroscience, March 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#44 of 1,347)
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

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3 news outlets
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4 X users
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1 YouTube creator

Citations

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42 Dimensions

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108 Mendeley
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Title
Evaluation of a Neuromechanical Walking Control Model Using Disturbance Experiments
Published in
Frontiers in Computational Neuroscience, March 2017
DOI 10.3389/fncom.2017.00015
Pubmed ID
Authors

Seungmoon Song, Hartmut Geyer

Abstract

Neuromechanical simulations have been used to study the spinal control of human locomotion which involves complex mechanical dynamics. So far, most neuromechanical simulation studies have focused on demonstrating the capability of a proposed control model in generating normal walking. As many of these models with competing control hypotheses can generate human-like normal walking behaviors, a more in-depth evaluation is required. Here, we conduct the more in-depth evaluation on a spinal-reflex-based control model using five representative gait disturbances, ranging from electrical stimulation to mechanical perturbation at individual leg joints and at the whole body. The immediate changes in muscle activations of the model are compared to those of humans across different gait phases and disturbance magnitudes. Remarkably similar response trends for the majority of investigated muscles and experimental conditions reinforce the plausibility of the reflex circuits of the model. However, the model's responses lack in amplitude for two experiments with whole body disturbances suggesting that in these cases the proposed reflex circuits need to be amplified by additional control structures such as location-specific cutaneous reflexes. A model that captures these selective amplifications would be able to explain both steady and reactive spinal control of human locomotion. Neuromechanical simulations that investigate hypothesized control models are complementary to gait experiments in better understanding the control of human locomotion.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Unknown 107 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 33 31%
Student > Master 14 13%
Researcher 11 10%
Student > Doctoral Student 9 8%
Student > Bachelor 6 6%
Other 12 11%
Unknown 23 21%
Readers by discipline Count As %
Engineering 53 49%
Neuroscience 11 10%
Nursing and Health Professions 3 3%
Sports and Recreations 3 3%
Computer Science 2 2%
Other 9 8%
Unknown 27 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 27. 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 09 April 2019.
All research outputs
#1,226,101
of 22,959,818 outputs
Outputs from Frontiers in Computational Neuroscience
#44
of 1,347 outputs
Outputs of similar age
#26,745
of 307,962 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#2
of 28 outputs
Altmetric has tracked 22,959,818 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,347 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has done particularly well, scoring higher than 96% 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 307,962 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.