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A Decoding Scheme for Incomplete Motor Imagery EEG With Deep Belief Network

Overview of attention for article published in Frontiers in Neuroscience, September 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

patent
2 patents

Citations

dimensions_citation
44 Dimensions

Readers on

mendeley
60 Mendeley
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Title
A Decoding Scheme for Incomplete Motor Imagery EEG With Deep Belief Network
Published in
Frontiers in Neuroscience, September 2018
DOI 10.3389/fnins.2018.00680
Pubmed ID
Authors

Yaqi Chu, Xingang Zhao, Yijun Zou, Weiliang Xu, Jianda Han, Yiwen Zhao

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 60 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 22%
Student > Master 8 13%
Student > Bachelor 6 10%
Researcher 4 7%
Other 2 3%
Other 2 3%
Unknown 25 42%
Readers by discipline Count As %
Engineering 23 38%
Computer Science 4 7%
Neuroscience 4 7%
Medicine and Dentistry 3 5%
Nursing and Health Professions 1 2%
Other 1 2%
Unknown 24 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 24 August 2023.
All research outputs
#5,450,007
of 25,385,509 outputs
Outputs from Frontiers in Neuroscience
#4,100
of 11,542 outputs
Outputs of similar age
#99,572
of 351,831 outputs
Outputs of similar age from Frontiers in Neuroscience
#93
of 254 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has gotten more attention than average, scoring higher than 64% 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 351,831 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 254 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.