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SVM-based classification method to identify alcohol consumption using ECG and PPG monitoring

Overview of attention for article published in Personal and Ubiquitous Computing, June 2017
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Mentioned by

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1 X user
facebook
1 Facebook page

Citations

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22 Dimensions

Readers on

mendeley
38 Mendeley
Title
SVM-based classification method to identify alcohol consumption using ECG and PPG monitoring
Published in
Personal and Ubiquitous Computing, June 2017
DOI 10.1007/s00779-017-1042-0
Authors

Wen-Fong Wang, Ching-Yu Yang, Yan-Fu Wu

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 21%
Student > Master 6 16%
Researcher 3 8%
Other 2 5%
Professor 2 5%
Other 5 13%
Unknown 12 32%
Readers by discipline Count As %
Computer Science 14 37%
Engineering 7 18%
Medicine and Dentistry 2 5%
Physics and Astronomy 1 3%
Neuroscience 1 3%
Other 1 3%
Unknown 12 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 28 June 2017.
All research outputs
#17,900,930
of 22,982,639 outputs
Outputs from Personal and Ubiquitous Computing
#592
of 1,192 outputs
Outputs of similar age
#226,377
of 315,496 outputs
Outputs of similar age from Personal and Ubiquitous Computing
#22
of 45 outputs
Altmetric has tracked 22,982,639 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,192 research outputs from this source. They receive a mean Attention Score of 2.8. This one is in the 26th percentile – i.e., 26% 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 315,496 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.