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Attention Score in Context
| Title |
Emergent Gait Strategies Defined by Cluster Analysis When Using Imperfect Exoskeleton Algorithms
|
|---|---|
| Published in |
IEEE Robotics and Automation Letters, February 2024
|
| DOI | 10.1109/lra.2024.3366010 |
| Authors |
Man I Wu, Leia Stirling |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 13 March 2024.
All research outputs
#1,617,725
of 25,482,409 outputs
Outputs from IEEE Robotics and Automation Letters
#132
of 2,584 outputs
Outputs of similar age
#17,898
of 264,654 outputs
Outputs of similar age from IEEE Robotics and Automation Letters
#2
of 58 outputs
Altmetric has tracked 25,482,409 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,584 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has done particularly well, scoring higher than 95% 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 264,654 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 58 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.