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A rapid and intelligent designing technique for patient-specific and 3D-printed orthopedic cast

Overview of attention for article published in 3D Printing in Medicine, December 2016
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About this Attention Score

  • Among the highest-scoring outputs from this source (#36 of 123)
  • Good Attention Score compared to outputs of the same age (70th percentile)

Mentioned by

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2 X users
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1 patent

Citations

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82 Dimensions

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165 Mendeley
Title
A rapid and intelligent designing technique for patient-specific and 3D-printed orthopedic cast
Published in
3D Printing in Medicine, December 2016
DOI 10.1186/s41205-016-0007-7
Pubmed ID
Authors

Hui Lin, Lin Shi, Defeng Wang

Abstract

Two point four out of 100 people suffer from one or more fractures in the course of average lifetimes. Traditional casts are featured as cumbersome structures that result in high risk of cutaneous complications. Clinical demands for developing a hygienic cast have gotten more and more attention. 3D printing technique is rapidly growing in the fabrication of custom-made rehabilitation tools. The objective of this study is to develop a rapid and intelligent modeling technique for developing patient-specific and hygienic orthopedic casts produced by 3D printing technologies. A cast model is firstly created from a patient's image to develop patient-specific features. A unique technique to creating geometric reference has been developed to perform detail modeling cast. The cast is modeled as funnel-shaped geometry to create smooth edges to prevent bruises from mild movements of injured limbs. Surface pattern includes ventilation structure and opening gap for hygienic purpose and wearing comfort. The cast can be adjusted to accommodate swelling from injured limbs during treatment. Finite element analysis (FEA) is employed to validate the mechanical performance of the cast structure and identify potential risk of the structural collapse due to concentrated stresses. The cast is fabricated by 3D printing technology using approval material. The 3D-printed prototype is featured as super lightweight with 1/10 of weight in compared with traditional alternatives. Medical technicians with few experiences can design cast within 20 min using the proposed technique. The image-based design minimizes the distortion during healing process because of the best fit geometry. The highly ventilated structure develops hygienic benefits on reducing the risk of cutaneous complications and potentially improve treatment efficacy and increase patients' satisfactions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users 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 165 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 165 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 30 18%
Student > Bachelor 28 17%
Student > Ph. D. Student 15 9%
Researcher 10 6%
Student > Doctoral Student 9 5%
Other 23 14%
Unknown 50 30%
Readers by discipline Count As %
Engineering 54 33%
Medicine and Dentistry 23 14%
Design 8 5%
Unspecified 7 4%
Biochemistry, Genetics and Molecular Biology 5 3%
Other 18 11%
Unknown 50 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 04 July 2023.
All research outputs
#6,879,015
of 24,041,016 outputs
Outputs from 3D Printing in Medicine
#36
of 123 outputs
Outputs of similar age
#121,365
of 423,688 outputs
Outputs of similar age from 3D Printing in Medicine
#4
of 4 outputs
Altmetric has tracked 24,041,016 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 123 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 68% 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 423,688 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.