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Future developments in brain-machine interface research

Overview of attention for article published in Clinics, January 2011
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#41 of 1,215)
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

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2 news outlets
blogs
2 blogs
twitter
5 X users
patent
4 patents

Citations

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98 Dimensions

Readers on

mendeley
293 Mendeley
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1 CiteULike
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Title
Future developments in brain-machine interface research
Published in
Clinics, January 2011
DOI 10.1590/s1807-59322011001300004
Pubmed ID
Authors

Mikhail A Lebedev, Andrew J Tate, Timothy L Hanson, Zheng Li, Joseph E O'Doherty, Jesse A Winans, Peter J Ifft, Katie Z Zhuang, Nathan A Fitzsimmons, David A Schwarz, Andrew M Fuller, Je Hi An, Miguel A L Nicolelis

Abstract

Neuroprosthetic devices based on brain-machine interface technology hold promise for the restoration of body mobility in patients suffering from devastating motor deficits caused by brain injury, neurologic diseases and limb loss. During the last decade, considerable progress has been achieved in this multidisciplinary research, mainly in the brain-machine interface that enacts upper-limb functionality. However, a considerable number of problems need to be resolved before fully functional limb neuroprostheses can be built. To move towards developing neuroprosthetic devices for humans, brain-machine interface research has to address a number of issues related to improving the quality of neuronal recordings, achieving stable, long-term performance, and extending the brain-machine interface approach to a broad range of motor and sensory functions. Here, we review the future steps that are part of the strategic plan of the Duke University Center for Neuroengineering, and its partners, the Brazilian National Institute of Brain-Machine Interfaces and the École Polytechnique Fédérale de Lausanne (EPFL) Center for Neuroprosthetics, to bring this new technology to clinical fruition.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 293 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 11 4%
Brazil 4 1%
Bangladesh 2 <1%
United Kingdom 2 <1%
Germany 1 <1%
China 1 <1%
Mexico 1 <1%
Unknown 271 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 73 25%
Student > Master 52 18%
Researcher 39 13%
Student > Bachelor 37 13%
Student > Postgraduate 16 5%
Other 40 14%
Unknown 36 12%
Readers by discipline Count As %
Engineering 101 34%
Agricultural and Biological Sciences 47 16%
Neuroscience 30 10%
Medicine and Dentistry 27 9%
Computer Science 15 5%
Other 26 9%
Unknown 47 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 34. 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 19 April 2022.
All research outputs
#1,169,301
of 25,371,288 outputs
Outputs from Clinics
#41
of 1,215 outputs
Outputs of similar age
#5,593
of 190,469 outputs
Outputs of similar age from Clinics
#4
of 77 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,215 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. 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 190,469 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 97% of its contemporaries.
We're also able to compare this research output to 77 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 94% of its contemporaries.