↓ Skip to main content

Advancing quantitative techniques to improve understanding of the skeletal structure-function relationship

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, March 2018
Altmetric Badge

Mentioned by

twitter
2 X users

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
46 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Advancing quantitative techniques to improve understanding of the skeletal structure-function relationship
Published in
Journal of NeuroEngineering and Rehabilitation, March 2018
DOI 10.1186/s12984-018-0368-9
Pubmed ID
Authors

Frances T. Sheehan, Elizabeth L. Brainerd, Karen L. Troy, Sandra J. Shefelbine, Janet L. Ronsky

Abstract

Although all functional movement arises from the interplay between the neurological, skeletal, and muscular systems, it is the skeletal system that forms the basic framework for functional movement. Central to understanding human neuromuscular development, along with the genesis of musculoskeletal pathologies, is quantifying how the human skeletal system adapts and mal-adapts to its mechanical environment. Advancing this understanding is hampered by an inability to directly and non-invasively measure in vivo strains, stresses, and forces on bone. Thus, we traditionally have turned to animal models to garner such information. These models enable direct in vivo measures that are not available for human subjects, providing information in regards to both skeletal adaptation and the interplay between the skeletal and muscular systems. Recently, there has been an explosion of new imaging and modeling techniques providing non-invasive, in vivo measures and estimates of skeletal form and function that have long been missing. Combining multiple modalities and techniques has proven to be one of our most valuable resources in enhancing our understanding of the form-function relationship of the human skeletal, muscular, and neurological systems. Thus, to continue advancing our knowledge of the structural-functional relationship, validation of current tools is needed, while development is required to limit the deficiencies in these tools and develop new ones.

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

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 20%
Student > Master 4 9%
Student > Bachelor 4 9%
Professor > Associate Professor 3 7%
Professor 2 4%
Other 8 17%
Unknown 16 35%
Readers by discipline Count As %
Engineering 8 17%
Medicine and Dentistry 4 9%
Biochemistry, Genetics and Molecular Biology 3 7%
Nursing and Health Professions 3 7%
Agricultural and Biological Sciences 2 4%
Other 6 13%
Unknown 20 43%
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 April 2018.
All research outputs
#15,495,840
of 23,028,364 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#848
of 1,293 outputs
Outputs of similar age
#212,196
of 332,278 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#21
of 29 outputs
Altmetric has tracked 23,028,364 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,293 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one is in the 26th percentile – i.e., 26% 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 332,278 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.