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Design of a Bio-Inspired Gait Phase Decoder Based on Temporal Convolution Network Architecture With Contralateral Surface Electromyography Toward Hip Prosthesis Control

Overview of attention for article published in Frontiers in Neurorobotics, May 2022
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4 X users

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11 Mendeley
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Title
Design of a Bio-Inspired Gait Phase Decoder Based on Temporal Convolution Network Architecture With Contralateral Surface Electromyography Toward Hip Prosthesis Control
Published in
Frontiers in Neurorobotics, May 2022
DOI 10.3389/fnbot.2022.791169
Pubmed ID
Authors

Yixi Chen, Xinwei Li, Hao Su, Dingguo Zhang, Hongliu Yu

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.
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 %
Professor 2 18%
Other 1 9%
Student > Master 1 9%
Unknown 7 64%
Readers by discipline Count As %
Engineering 3 27%
Nursing and Health Professions 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 01 June 2022.
All research outputs
#14,556,454
of 23,312,088 outputs
Outputs from Frontiers in Neurorobotics
#357
of 905 outputs
Outputs of similar age
#214,229
of 442,429 outputs
Outputs of similar age from Frontiers in Neurorobotics
#26
of 54 outputs
Altmetric has tracked 23,312,088 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 905 research outputs from this source. They receive a mean Attention Score of 4.1. 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 442,429 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 54 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 50% of its contemporaries.