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Functional principal component analysis as a new methodology for the analysis of the impact of two rehabilitation protocols in functional recovery after stroke

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, September 2014
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Title
Functional principal component analysis as a new methodology for the analysis of the impact of two rehabilitation protocols in functional recovery after stroke
Published in
Journal of NeuroEngineering and Rehabilitation, September 2014
DOI 10.1186/1743-0003-11-134
Pubmed ID
Authors

M Luz Sánchez-Sánchez, Juan-Manuel Belda-Lois, Silvia Mena-del Horno, Enrique Viosca-Herrero, Beatriz Gisbert-Morant, Celedonia Igual-Camacho, Ignacio Bermejo-Bosch

Abstract

This study addressed the problem of evaluating the effectiveness of two protocols of physiotherapy for functional recovery after stroke. In particular, the study explored the use of Functional Principal Component Analysis (FPCA), a multivariate data analysis in order to assess and clarify the process of regaining independence after stroke.

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 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 1%
Unknown 91 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 18%
Researcher 12 13%
Student > Bachelor 12 13%
Student > Ph. D. Student 11 12%
Student > Postgraduate 4 4%
Other 13 14%
Unknown 23 25%
Readers by discipline Count As %
Nursing and Health Professions 14 15%
Medicine and Dentistry 14 15%
Engineering 9 10%
Neuroscience 6 7%
Sports and Recreations 6 7%
Other 17 18%
Unknown 26 28%
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 13 June 2016.
All research outputs
#22,756,649
of 25,371,288 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#1,264
of 1,413 outputs
Outputs of similar age
#214,637
of 250,370 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#17
of 21 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,413 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 1st percentile – i.e., 1% 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 250,370 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.