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EEG-Based Mental Workload Neurometric to Evaluate the Impact of Different Traffic and Road Conditions in Real Driving Settings

Overview of attention for article published in Frontiers in Human Neuroscience, December 2018
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

Mentioned by

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3 X users

Readers on

mendeley
156 Mendeley
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Title
EEG-Based Mental Workload Neurometric to Evaluate the Impact of Different Traffic and Road Conditions in Real Driving Settings
Published in
Frontiers in Human Neuroscience, December 2018
DOI 10.3389/fnhum.2018.00509
Pubmed ID
Authors

Gianluca Di Flumeri, Gianluca Borghini, Pietro Aricò, Nicolina Sciaraffa, Paola Lanzi, Simone Pozzi, Valeria Vignali, Claudio Lantieri, Arianna Bichicchi, Andrea Simone, Fabio Babiloni

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 156 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 156 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 38 24%
Student > Master 16 10%
Researcher 15 10%
Student > Bachelor 11 7%
Student > Doctoral Student 6 4%
Other 21 13%
Unknown 49 31%
Readers by discipline Count As %
Engineering 36 23%
Computer Science 19 12%
Neuroscience 14 9%
Psychology 11 7%
Medicine and Dentistry 7 4%
Other 13 8%
Unknown 56 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 12 February 2019.
All research outputs
#12,820,491
of 23,117,738 outputs
Outputs from Frontiers in Human Neuroscience
#3,442
of 7,221 outputs
Outputs of similar age
#192,863
of 435,331 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#45
of 107 outputs
Altmetric has tracked 23,117,738 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,221 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one has gotten more attention than average, scoring higher than 51% 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 435,331 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 55% of its contemporaries.
We're also able to compare this research output to 107 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 56% of its contemporaries.