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A Characterization of Brain-Computer Interface Performance Trade-Offs Using Support Vector Machines and Deep Neural Networks to Decode Movement Intent

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

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

Mentioned by

patent
4 patents

Citations

dimensions_citation
32 Dimensions

Readers on

mendeley
51 Mendeley
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Title
A Characterization of Brain-Computer Interface Performance Trade-Offs Using Support Vector Machines and Deep Neural Networks to Decode Movement Intent
Published in
Frontiers in Neuroscience, October 2018
DOI 10.3389/fnins.2018.00763
Pubmed ID
Authors

Nicholas D. Skomrock, Michael A. Schwemmer, Jordyn E. Ting, Hemang R. Trivedi, Gaurav Sharma, Marcia A. Bockbrader, David A. Friedenberg

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 18%
Professor > Associate Professor 4 8%
Student > Bachelor 4 8%
Other 3 6%
Student > Master 3 6%
Other 9 18%
Unknown 19 37%
Readers by discipline Count As %
Engineering 10 20%
Neuroscience 5 10%
Medicine and Dentistry 3 6%
Computer Science 2 4%
Physics and Astronomy 1 2%
Other 3 6%
Unknown 27 53%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 12 September 2023.
All research outputs
#8,538,940
of 25,385,509 outputs
Outputs from Frontiers in Neuroscience
#5,437
of 11,542 outputs
Outputs of similar age
#144,600
of 361,740 outputs
Outputs of similar age from Frontiers in Neuroscience
#121
of 266 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
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 51% 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 361,740 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 52% of its contemporaries.
We're also able to compare this research output to 266 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 53% of its contemporaries.