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Real time electrocardiogram QRS detection using combined adaptive threshold

Overview of attention for article published in BioMedical Engineering OnLine, August 2004
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#17 of 759)
  • High Attention Score compared to outputs of the same age (91st percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
1 tweeter
patent
4 patents

Citations

dimensions_citation
234 Dimensions

Readers on

mendeley
252 Mendeley
citeulike
6 CiteULike
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Title
Real time electrocardiogram QRS detection using combined adaptive threshold
Published in
BioMedical Engineering OnLine, August 2004
DOI 10.1186/1475-925x-3-28
Pubmed ID
Authors

Ivaylo I Christov

Abstract

QRS and ventricular beat detection is a basic procedure for electrocardiogram (ECG) processing and analysis. Large variety of methods have been proposed and used, featuring high percentages of correct detection. Nevertheless, the problem remains open especially with respect to higher detection accuracy in noisy ECGs

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 252 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
Colombia 3 1%
Germany 2 <1%
Switzerland 2 <1%
Spain 2 <1%
Lithuania 1 <1%
Czechia 1 <1%
Canada 1 <1%
Netherlands 1 <1%
Other 2 <1%
Unknown 234 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 69 27%
Student > Master 49 19%
Researcher 45 18%
Student > Bachelor 22 9%
Student > Doctoral Student 10 4%
Other 35 14%
Unknown 22 9%
Readers by discipline Count As %
Engineering 117 46%
Computer Science 37 15%
Medicine and Dentistry 20 8%
Agricultural and Biological Sciences 17 7%
Neuroscience 9 4%
Other 20 8%
Unknown 32 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 December 2021.
All research outputs
#1,235,777
of 19,548,179 outputs
Outputs from BioMedical Engineering OnLine
#17
of 759 outputs
Outputs of similar age
#18,825
of 235,254 outputs
Outputs of similar age from BioMedical Engineering OnLine
#1
of 1 outputs
Altmetric has tracked 19,548,179 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 759 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done particularly well, scoring higher than 97% 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 235,254 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 1 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