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Mechanical characterization of brain tissue in tension at dynamic strain rates

Overview of attention for article published in Journal of the Mechanical Behavior of Biomedical Materials, September 2012
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  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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2 X users
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1 Wikipedia page

Citations

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186 Dimensions

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314 Mendeley
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Title
Mechanical characterization of brain tissue in tension at dynamic strain rates
Published in
Journal of the Mechanical Behavior of Biomedical Materials, September 2012
DOI 10.1016/j.jmbbm.2012.07.015
Pubmed ID
Authors

Badar Rashid, Michel Destrade, Michael D Gilchrist

Abstract

Mechanical characterization of brain tissue at high loading velocities is crucial for modeling Traumatic Brain Injury (TBI). During severe impact conditions, brain tissue experiences compression, tension and shear. Limited experimental data is available for brain tissue in extension at dynamic strain rates. In this research, a High Rate Tension Device (HRTD) was developed to obtain dynamic properties of brain tissue in extension at strain rates of ≤90/s. In vitro tensile tests were performed to obtain properties of brain tissue at strain rates of 30, 60 and 90/s up to 30% strain. The brain tissue showed a stiffer response with increasing strain rates, showing that hyperelastic models are not adequate. Specifically, the tensile engineering stress at 30% strain was 3.1±0.49kPa, 4.3±0.86kPa, 6.5±0.76kPa (mean±SD) at strain rates of 30, 60 and 90/s, respectively. Force relaxation tests in tension were also conducted at different strain magnitudes (10-60% strain) with the average rise time of 24ms, which were used to derive time dependent parameters. One-term Ogden, Fung and Gent models were used to obtain material parameters from the experimental data. Numerical simulations were performed using a one-term Ogden model to analyze hyperelastic behavior of brain tissue up to 30% strain. The material parameters obtained in this study will help to develop biofidelic human brain finite element models, which can subsequently be used to predict brain injuries under impact conditions and as a reconstruction and simulation tool for forensic investigations.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 314 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 <1%
United Kingdom 1 <1%
Turkey 1 <1%
Russia 1 <1%
Luxembourg 1 <1%
Unknown 307 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 86 27%
Researcher 44 14%
Student > Master 43 14%
Student > Bachelor 30 10%
Student > Doctoral Student 14 4%
Other 42 13%
Unknown 55 18%
Readers by discipline Count As %
Engineering 155 49%
Agricultural and Biological Sciences 24 8%
Materials Science 16 5%
Neuroscience 10 3%
Medicine and Dentistry 9 3%
Other 29 9%
Unknown 71 23%
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 03 September 2020.
All research outputs
#7,778,071
of 25,371,288 outputs
Outputs from Journal of the Mechanical Behavior of Biomedical Materials
#278
of 1,333 outputs
Outputs of similar age
#56,743
of 186,807 outputs
Outputs of similar age from Journal of the Mechanical Behavior of Biomedical Materials
#1
of 8 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,333 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 78% 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 186,807 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 69% of its contemporaries.
We're also able to compare this research output to 8 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