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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Smithsonian figshare
Dataset . 2020
License: CC BY
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Data for: Geometrical parameters for musculoskeletal modeling of hand

Authors: Havelková L.; Zítka T.; Fiala P.; Rybarova M.; Tupý R.; Kalis V.; Ismail K.M.;

Data for: Geometrical parameters for musculoskeletal modeling of hand

Abstract

Dataset to be linked with not yet published manuscript "Geometrical parameters for musculoskeletal modeling of hand" In musculoskeletal modelling, parameters identification, such as the exact position and trajectories of muscle attachments, is a crucial issue. The main goal of this study was to calculate the position, attachment dimensions and cross section areas of twenty-five extrinsic and intrinsic hand muscle complexes. We integrated measurements taken from cadaveric preparations, magnetic resonance imaging and mathematical theory. Sixteen cadaveric preparations were dissected to draw up the anatomical maps including the position of muscle attachments, dimensions, shapes, cross section areas and variations. The magnetic resonance imaging of cadaveric upper extremity was performed to reconstruct the geometry of all bones and hand muscles. Using these outcomes, the muscle attachments and cross section areas were extracted and verified using the obtained morphological and morphometric analysis. The exact trajectories of muscle lines of action were computed using the modified weighted k-means method and Hungary algorithm. This work introduces a new approach to acquiring musculoskeletal modelling data in general and contributes extensive dataset to the hand musculature modelling in particular. Acknowledgments This work was supported by the project n. 182 “Obstetrics 2.0 - Virtual models for the prevention of injuries during childbirth” realised within the frame of the Program INTERREG V-A: Cross- border cooperation between the Czech Republic and the Federal State of Germany Bavaria, Aim European Cross-border cooperation 2014-2020. The realisation is supported by financial means of the European Regional Development Fund (85 % of the costs) and the state budget of the Czech Republic (5 %). KI is part-funded by project No. CZ.02.1.01/0.0/0.0/16_019/0000787 “Fighting INfectious Diseases“, awarded by the Ministry of Education, Youth and Sports of the Czech Republic, financed from The European Regional Development Fund.

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Keywords

Physiology, k-means method, Information Systems not elsewhere classified, musculoskeletal modelling, muscle origins, insertions, Cell Biology, muscle trajectory, Mathematical Sciences not elsewhere classified, muscle origins, Hungary algorithm, cross section area of muscle, Environmental Sciences not elsewhere classified, insertions, Medicine, hand model, Biological Sciences not elsewhere classified, MRI

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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