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Evaluation of Three Machine Learning Algorithms for the Automatic Classification of EMG Patterns in Gait Disorders

Overview of attention for article published in Frontiers in Neurology, May 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

Mentioned by

twitter
5 X users

Readers on

mendeley
61 Mendeley
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Title
Evaluation of Three Machine Learning Algorithms for the Automatic Classification of EMG Patterns in Gait Disorders
Published in
Frontiers in Neurology, May 2021
DOI 10.3389/fneur.2021.666458
Pubmed ID
Authors

Christopher Fricke, Jalal Alizadeh, Nahrin Zakhary, Timo B. Woost, Martin Bogdan, Joseph Classen

Timeline

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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.
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 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 61 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 10%
Student > Bachelor 5 8%
Lecturer 3 5%
Researcher 3 5%
Student > Master 3 5%
Other 6 10%
Unknown 35 57%
Readers by discipline Count As %
Engineering 12 20%
Nursing and Health Professions 3 5%
Computer Science 2 3%
Linguistics 1 2%
Environmental Science 1 2%
Other 5 8%
Unknown 37 61%
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 03 May 2022.
All research outputs
#13,510,424
of 23,308,124 outputs
Outputs from Frontiers in Neurology
#5,163
of 12,222 outputs
Outputs of similar age
#197,125
of 445,980 outputs
Outputs of similar age from Frontiers in Neurology
#191
of 597 outputs
Altmetric has tracked 23,308,124 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,222 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has gotten more attention than average, scoring higher than 56% 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 445,980 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 54% of its contemporaries.
We're also able to compare this research output to 597 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 65% of its contemporaries.