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Review of control strategies for robotic movement training after neurologic injury

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, June 2009
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

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2 X users
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3 patents
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3 Wikipedia pages

Citations

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900 Dimensions

Readers on

mendeley
1155 Mendeley
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3 CiteULike
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Title
Review of control strategies for robotic movement training after neurologic injury
Published in
Journal of NeuroEngineering and Rehabilitation, June 2009
DOI 10.1186/1743-0003-6-20
Pubmed ID
Authors

Laura Marchal-Crespo, David J Reinkensmeyer

Abstract

There is increasing interest in using robotic devices to assist in movement training following neurologic injuries such as stroke and spinal cord injury. This paper reviews control strategies for robotic therapy devices. Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching. The greatest amount of work has been done on developing assistive strategies, and thus the majority of this review summarizes techniques for implementing assistive strategies, including impedance-, counterbalance-, and EMG- based controllers, as well as adaptive controllers that modify control parameters based on ongoing participant performance. Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others. It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training. In future research, there is a need for head-to-head comparison of control algorithms in randomized, controlled clinical trials, and for improved models of human motor recovery to provide a more rational framework for designing robotic therapy control strategies.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1,155 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 <1%
Switzerland 7 <1%
Italy 6 <1%
Germany 4 <1%
United Kingdom 4 <1%
Malaysia 3 <1%
Brazil 3 <1%
Spain 2 <1%
Canada 2 <1%
Other 17 1%
Unknown 1098 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 288 25%
Student > Master 208 18%
Researcher 142 12%
Student > Bachelor 96 8%
Student > Doctoral Student 68 6%
Other 168 15%
Unknown 185 16%
Readers by discipline Count As %
Engineering 641 55%
Medicine and Dentistry 64 6%
Computer Science 41 4%
Neuroscience 36 3%
Agricultural and Biological Sciences 32 3%
Other 114 10%
Unknown 227 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 January 2024.
All research outputs
#2,696,115
of 22,758,963 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#135
of 1,278 outputs
Outputs of similar age
#9,159
of 98,608 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#2
of 9 outputs
Altmetric has tracked 22,758,963 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,278 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done well, scoring higher than 89% 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 98,608 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 90% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 7 of them.