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A real-time system for biomechanical analysis of human movement and muscle function

Overview of attention for article published in Medical & Biological Engineering & Computing, July 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)

Mentioned by

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2 X users
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2 patents
wikipedia
1 Wikipedia page

Citations

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288 Dimensions

Readers on

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479 Mendeley
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1 CiteULike
Title
A real-time system for biomechanical analysis of human movement and muscle function
Published in
Medical & Biological Engineering & Computing, July 2013
DOI 10.1007/s11517-013-1076-z
Pubmed ID
Authors

Antonie J. van den Bogert, Thomas Geijtenbeek, Oshri Even-Zohar, Frans Steenbrink, Elizabeth C. Hardin

Abstract

Mechanical analysis of movement plays an important role in clinical management of neurological and orthopedic conditions. There has been increasing interest in performing movement analysis in real-time, to provide immediate feedback to both therapist and patient. However, such work to date has been limited to single-joint kinematics and kinetics. Here we present a software system, named human body model (HBM), to compute joint kinematics and kinetics for a full body model with 44 degrees of freedom, in real-time, and to estimate length changes and forces in 300 muscle elements. HBM was used to analyze lower extremity function during gait in 12 able-bodied subjects. Processing speed exceeded 120 samples per second on standard PC hardware. Joint angles and moments were consistent within the group, and consistent with other studies in the literature. Estimated muscle force patterns were consistent among subjects and agreed qualitatively with electromyography, to the extent that can be expected from a biomechanical model. The real-time analysis was integrated into the D-Flow system for development of custom real-time feedback applications and into the gait real-time analysis interactive lab system for gait analysis and gait retraining.

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

Geographical breakdown

Country Count As %
United States 5 1%
Germany 3 <1%
Netherlands 2 <1%
Switzerland 2 <1%
France 2 <1%
United Kingdom 2 <1%
Brazil 1 <1%
Finland 1 <1%
Austria 1 <1%
Other 4 <1%
Unknown 456 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 118 25%
Student > Master 78 16%
Researcher 55 11%
Student > Bachelor 37 8%
Student > Doctoral Student 28 6%
Other 79 16%
Unknown 84 18%
Readers by discipline Count As %
Engineering 160 33%
Sports and Recreations 43 9%
Medicine and Dentistry 40 8%
Computer Science 30 6%
Nursing and Health Professions 22 5%
Other 59 12%
Unknown 125 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 07 July 2020.
All research outputs
#5,165,601
of 25,373,627 outputs
Outputs from Medical & Biological Engineering & Computing
#160
of 2,053 outputs
Outputs of similar age
#41,787
of 209,986 outputs
Outputs of similar age from Medical & Biological Engineering & Computing
#1
of 1 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,053 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done particularly well, scoring higher than 92% 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 209,986 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 1 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