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To Inform or to Instruct? An Evaluation of Meaningful Vibrotactile Patterns to Support Automated Vehicle Takeover Performance

Overview of attention for article published in IEEE Transactions on Human-Machine Systems, September 2022
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
19 Mendeley
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Title
To Inform or to Instruct? An Evaluation of Meaningful Vibrotactile Patterns to Support Automated Vehicle Takeover Performance
Published in
IEEE Transactions on Human-Machine Systems, September 2022
DOI 10.1109/thms.2022.3205880
Authors

Gaojian Huang, Brandon J. Pitts

Timeline

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

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 16%
Student > Doctoral Student 2 11%
Researcher 2 11%
Professor 1 5%
Student > Master 1 5%
Other 1 5%
Unknown 9 47%
Readers by discipline Count As %
Engineering 4 21%
Computer Science 2 11%
Design 2 11%
Psychology 1 5%
Unknown 10 53%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 04 October 2022.
All research outputs
#7,857,016
of 25,392,582 outputs
Outputs from IEEE Transactions on Human-Machine Systems
#124
of 473 outputs
Outputs of similar age
#140,987
of 438,014 outputs
Outputs of similar age from IEEE Transactions on Human-Machine Systems
#1
of 6 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 473 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 73% 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 438,014 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 67% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them