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An Algorithm for Accurate Marker-Based Gait Event Detection in Healthy and Pathological Populations During Complex Motor Tasks

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, June 2022
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

twitter
19 X users

Citations

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9 Dimensions

Readers on

mendeley
51 Mendeley
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Title
An Algorithm for Accurate Marker-Based Gait Event Detection in Healthy and Pathological Populations During Complex Motor Tasks
Published in
Frontiers in Bioengineering and Biotechnology, June 2022
DOI 10.3389/fbioe.2022.868928
Pubmed ID
Authors

Tecla Bonci, Francesca Salis, Kirsty Scott, Lisa Alcock, Clemens Becker, Stefano Bertuletti, Ellen Buckley, Marco Caruso, Andrea Cereatti, Silvia Del Din, Eran Gazit, Clint Hansen, Jeffrey M. Hausdorff, Walter Maetzler, Luca Palmerini, Lynn Rochester, Lars Schwickert, Basil Sharrack, Ioannis Vogiatzis, Claudia Mazzà

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 19 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 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 %
Researcher 8 16%
Unspecified 6 12%
Student > Ph. D. Student 4 8%
Other 2 4%
Student > Postgraduate 2 4%
Other 2 4%
Unknown 27 53%
Readers by discipline Count As %
Unspecified 6 12%
Engineering 6 12%
Medicine and Dentistry 4 8%
Computer Science 2 4%
Neuroscience 2 4%
Other 2 4%
Unknown 29 57%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 20 June 2022.
All research outputs
#2,600,038
of 25,278,281 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#326
of 8,381 outputs
Outputs of similar age
#55,632
of 437,035 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#10
of 606 outputs
Altmetric has tracked 25,278,281 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,381 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 96% 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 437,035 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 606 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.