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A sequential learning model with GNN for EEG-EMG-based stroke rehabilitation BCI

Overview of attention for article published in Frontiers in Neuroscience, April 2023
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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 (59th percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
11 Mendeley
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Title
A sequential learning model with GNN for EEG-EMG-based stroke rehabilitation BCI
Published in
Frontiers in Neuroscience, April 2023
DOI 10.3389/fnins.2023.1125230
Pubmed ID
Authors

Haoyang Li, Hongfei Ji, Jian Yu, Jie Li, Lingjing Jin, Lingyu Liu, Zhongfei Bai, Chen Ye

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

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 9%
Student > Ph. D. Student 1 9%
Professor > Associate Professor 1 9%
Lecturer 1 9%
Unknown 7 64%
Readers by discipline Count As %
Unspecified 1 9%
Computer Science 1 9%
Neuroscience 1 9%
Medicine and Dentistry 1 9%
Unknown 7 64%
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 07 May 2023.
All research outputs
#15,533,143
of 25,394,764 outputs
Outputs from Frontiers in Neuroscience
#6,612
of 11,543 outputs
Outputs of similar age
#196,673
of 413,780 outputs
Outputs of similar age from Frontiers in Neuroscience
#160
of 403 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,543 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 42nd percentile – i.e., 42% 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 413,780 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 50% of its contemporaries.
We're also able to compare this research output to 403 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 59% of its contemporaries.