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Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients

Overview of attention for article published in Scientific Reports, August 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 (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
194 news outlets
blogs
16 blogs
twitter
342 X users
patent
8 patents
facebook
31 Facebook pages
googleplus
10 Google+ users
video
1 YouTube creator

Citations

dimensions_citation
326 Dimensions

Readers on

mendeley
774 Mendeley
citeulike
1 CiteULike
Title
Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients
Published in
Scientific Reports, August 2016
DOI 10.1038/srep30383
Pubmed ID
Authors

Ana R. C. Donati, Solaiman Shokur, Edgard Morya, Debora S. F. Campos, Renan C. Moioli, Claudia M. Gitti, Patricia B. Augusto, Sandra Tripodi, Cristhiane G. Pires, Gislaine A. Pereira, Fabricio L. Brasil, Simone Gallo, Anthony A. Lin, Angelo K. Takigami, Maria A. Aratanha, Sanjay Joshi, Hannes Bleuler, Gordon Cheng, Alan Rudolph, Miguel A. L. Nicolelis

X Demographics

X Demographics

The data shown below were collected from the profiles of 342 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 774 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 <1%
Singapore 2 <1%
Ireland 1 <1%
Brazil 1 <1%
France 1 <1%
United Kingdom 1 <1%
Switzerland 1 <1%
Israel 1 <1%
Canada 1 <1%
Other 0 0%
Unknown 762 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 129 17%
Student > Master 125 16%
Researcher 99 13%
Student > Bachelor 88 11%
Student > Doctoral Student 36 5%
Other 114 15%
Unknown 183 24%
Readers by discipline Count As %
Engineering 159 21%
Neuroscience 93 12%
Medicine and Dentistry 82 11%
Agricultural and Biological Sciences 49 6%
Psychology 35 5%
Other 145 19%
Unknown 211 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1856. 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 17 March 2024.
All research outputs
#5,316
of 25,551,063 outputs
Outputs from Scientific Reports
#83
of 141,712 outputs
Outputs of similar age
#46
of 369,760 outputs
Outputs of similar age from Scientific Reports
#2
of 3,712 outputs
Altmetric has tracked 25,551,063 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 141,712 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.8. This one has done particularly well, scoring higher than 99% 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 369,760 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 99% of its contemporaries.
We're also able to compare this research output to 3,712 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 99% of its contemporaries.