↓ Skip to main content

Interpreting Deep Learning Features for Myoelectric Control: A Comparison With Handcrafted Features

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, March 2020
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

twitter
4 X users

Readers on

mendeley
111 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Interpreting Deep Learning Features for Myoelectric Control: A Comparison With Handcrafted Features
Published in
Frontiers in Bioengineering and Biotechnology, March 2020
DOI 10.3389/fbioe.2020.00158
Pubmed ID
Authors

Ulysse Côté-Allard, Evan Campbell, Angkoon Phinyomark, François Laviolette, Benoit Gosselin, Erik Scheme

Timeline

Login to access the full chart related to this output.

If you don’t have an account, click here to discover Explorer

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 111 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 19%
Student > Master 16 14%
Researcher 9 8%
Professor > Associate Professor 7 6%
Lecturer 5 5%
Other 16 14%
Unknown 37 33%
Readers by discipline Count As %
Engineering 41 37%
Computer Science 15 14%
Neuroscience 4 4%
Biochemistry, Genetics and Molecular Biology 2 2%
Psychology 1 <1%
Other 3 3%
Unknown 45 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 05 October 2021.
All research outputs
#15,179,141
of 25,387,668 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#2,014
of 8,509 outputs
Outputs of similar age
#199,838
of 384,883 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#161
of 334 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,509 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done well, scoring higher than 75% 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 384,883 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 334 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 51% of its contemporaries.