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Patient specific ankle-foot orthoses using rapid prototyping

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, January 2011
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Mentioned by

twitter
1 tweeter

Citations

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169 Dimensions

Readers on

mendeley
269 Mendeley
citeulike
1 CiteULike
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Title
Patient specific ankle-foot orthoses using rapid prototyping
Published in
Journal of NeuroEngineering and Rehabilitation, January 2011
DOI 10.1186/1743-0003-8-1
Pubmed ID
Authors

Constantinos Mavroidis, Richard G Ranky, Mark L Sivak, Benjamin L Patritti, Joseph DiPisa, Alyssa Caddle, Kara Gilhooly, Lauren Govoni, Seth Sivak, Michael Lancia, Robert Drillio, Paolo Bonato

Abstract

Prefabricated orthotic devices are currently designed to fit a range of patients and therefore they do not provide individualized comfort and function. Custom-fit orthoses are superior to prefabricated orthotic devices from both of the above-mentioned standpoints. However, creating a custom-fit orthosis is a laborious and time-intensive manual process performed by skilled orthotists. Besides, adjustments made to both prefabricated and custom-fit orthoses are carried out in a qualitative manner. So both comfort and function can potentially suffer considerably. A computerized technique for fabricating patient-specific orthotic devices has the potential to provide excellent comfort and allow for changes in the standard design to meet the specific needs of each patient.

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

Geographical breakdown

Country Count As %
Italy 1 <1%
United Kingdom 1 <1%
Libya 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 264 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 47 17%
Student > Master 46 17%
Student > Bachelor 39 14%
Researcher 34 13%
Professor > Associate Professor 13 5%
Other 47 17%
Unknown 43 16%
Readers by discipline Count As %
Engineering 129 48%
Medicine and Dentistry 24 9%
Nursing and Health Professions 15 6%
Design 14 5%
Computer Science 6 2%
Other 22 8%
Unknown 59 22%

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 March 2015.
All research outputs
#2,582,433
of 4,866,695 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#207
of 365 outputs
Outputs of similar age
#82,941
of 146,222 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#12
of 16 outputs
Altmetric has tracked 4,866,695 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 365 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 25th percentile – i.e., 25% 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 146,222 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.