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Using hierarchical clustering methods to classify motor activities of COPD patients from wearable sensor data

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, June 2005
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Mentioned by

patent
1 patent

Citations

dimensions_citation
45 Dimensions

Readers on

mendeley
102 Mendeley
citeulike
3 CiteULike
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Title
Using hierarchical clustering methods to classify motor activities of COPD patients from wearable sensor data
Published in
Journal of NeuroEngineering and Rehabilitation, June 2005
DOI 10.1186/1743-0003-2-16
Pubmed ID
Authors

Delsey M Sherrill, Marilyn L Moy, John J Reilly, Paolo Bonato

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
United States 2 2%
Portugal 1 <1%
Italy 1 <1%
Germany 1 <1%
Spain 1 <1%
France 1 <1%
Unknown 93 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 22%
Researcher 16 16%
Student > Master 13 13%
Unspecified 9 9%
Student > Bachelor 8 8%
Other 21 21%
Unknown 13 13%
Readers by discipline Count As %
Engineering 28 27%
Computer Science 19 19%
Medicine and Dentistry 10 10%
Unspecified 9 9%
Nursing and Health Professions 3 3%
Other 16 16%
Unknown 17 17%
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 09 July 2019.
All research outputs
#7,610,760
of 23,205,257 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#506
of 1,298 outputs
Outputs of similar age
#20,328
of 56,963 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#3
of 9 outputs
Altmetric has tracked 23,205,257 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 1,298 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has gotten more attention than average, scoring higher than 57% 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 56,963 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.