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Predicting Driver's mental workload using physiological signals: A functional data analysis approach

Overview of attention for article published in Applied Ergonomics, March 2024
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)

Mentioned by

twitter
2 X users

Readers on

mendeley
3 Mendeley
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Title
Predicting Driver's mental workload using physiological signals: A functional data analysis approach
Published in
Applied Ergonomics, March 2024
DOI 10.1016/j.apergo.2024.104274
Pubmed ID
Authors

Chaeyoung Lee, MinJu Shin, David Eniyandunmo, Alvee Anwar, Eunsik Kim, Kyongwon Kim, Jae Keun Yoo, Chris Lee

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 67%
Lecturer 1 33%
Readers by discipline Count As %
Unspecified 2 67%
Engineering 1 33%
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 22 March 2024.
All research outputs
#15,651,551
of 25,576,801 outputs
Outputs from Applied Ergonomics
#1,149
of 1,679 outputs
Outputs of similar age
#69,253
of 171,828 outputs
Outputs of similar age from Applied Ergonomics
#2
of 3 outputs
Altmetric has tracked 25,576,801 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 1,679 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one is in the 29th percentile – i.e., 29% 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 171,828 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 58% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.