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Lower Limb Kinematics Trajectory Prediction Using Long Short-Term Memory Neural Networks

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, May 2020
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2 X users

Citations

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35 Dimensions

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67 Mendeley
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Title
Lower Limb Kinematics Trajectory Prediction Using Long Short-Term Memory Neural Networks
Published in
Frontiers in Bioengineering and Biotechnology, May 2020
DOI 10.3389/fbioe.2020.00362
Pubmed ID
Authors

Abdelrahman Zaroug, Daniel T. H. Lai, Kurt Mudie, Rezaul Begg

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 18%
Researcher 9 13%
Student > Bachelor 6 9%
Student > Ph. D. Student 6 9%
Student > Postgraduate 4 6%
Other 10 15%
Unknown 20 30%
Readers by discipline Count As %
Engineering 22 33%
Computer Science 4 6%
Medicine and Dentistry 3 4%
Unspecified 3 4%
Nursing and Health Professions 3 4%
Other 7 10%
Unknown 25 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 10 May 2020.
All research outputs
#18,718,509
of 23,201,298 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#3,484
of 6,883 outputs
Outputs of similar age
#288,522
of 382,949 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#249
of 393 outputs
Altmetric has tracked 23,201,298 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,883 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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 382,949 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 393 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.