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Control of Dynamic Limb Motion Using Fatigue-Resistant Asynchronous Intrafascicular Multi-Electrode Stimulation

Overview of attention for article published in Frontiers in Neuroscience, September 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
7 news outlets
blogs
2 blogs
twitter
4 X users
wikipedia
1 Wikipedia page

Readers on

mendeley
49 Mendeley
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Title
Control of Dynamic Limb Motion Using Fatigue-Resistant Asynchronous Intrafascicular Multi-Electrode Stimulation
Published in
Frontiers in Neuroscience, September 2016
DOI 10.3389/fnins.2016.00414
Pubmed ID
Authors

Mitchell A. Frankel, V John Mathews, Gregory A. Clark, Richard A. Normann, Sanford G. Meek

Abstract

Asynchronous intrafascicular multi-electrode stimulation (aIFMS) of small independent populations of peripheral nerve motor axons can evoke selective, fatigue-resistant muscle forces. We previously developed a real-time proportional closed-loop control method for aIFMS generation of isometric muscle force and the present work extends and adapts this closed-loop controller to the more demanding task of dynamically controlling joint position in the presence of opposing joint torque. A proportional-integral-velocity controller, with integrator anti-windup strategies, was experimentally validated as a means to evoke motion about the hind-limb ankle joint of an anesthetized feline via aIFMS stimulation of fast-twitch plantar-flexor muscles. The controller was successful in evoking steps in joint position with 2.4% overshoot, 2.3-s rise time, 4.5-s settling time, and near-zero steady-state error. Controlled step responses were consistent across changes in step size, stable against external disturbances, and reliable over time. The controller was able to evoke smooth eccentric motion at joint velocities up to 8 deg./s, as well as sinusoidal trajectories with frequencies up to 0.1 Hz, with time delays less than 1.5 s. These experiments provide important insights toward creating a robust closed-loop aIFMS controller that can evoke precise fatigue-resistant motion in paralyzed individuals, despite the complexities introduced by aIFMS.

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 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 48 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 24%
Student > Master 7 14%
Student > Doctoral Student 6 12%
Student > Bachelor 6 12%
Researcher 4 8%
Other 6 12%
Unknown 8 16%
Readers by discipline Count As %
Engineering 22 45%
Medicine and Dentistry 6 12%
Sports and Recreations 4 8%
Nursing and Health Professions 4 8%
Agricultural and Biological Sciences 3 6%
Other 0 0%
Unknown 10 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 69. 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 08 July 2019.
All research outputs
#618,542
of 25,374,917 outputs
Outputs from Frontiers in Neuroscience
#254
of 11,541 outputs
Outputs of similar age
#11,754
of 330,894 outputs
Outputs of similar age from Frontiers in Neuroscience
#5
of 132 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,541 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has done particularly well, scoring higher than 97% 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 330,894 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 96% of its contemporaries.
We're also able to compare this research output to 132 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 96% of its contemporaries.