A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction

Human Muscular Manipulability is a metric that measures the comfort of an specific pose and it can be used for a variety of applications related to healthcare. For this reason, we introduce KIMHu: a Kinematic, Imaging and electroMyography dataset for Human muscular manipulability index prediction. T...

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Autores principales: Hernández, Óscar G., Lopez-Castellanos, Jose M., Jara, Carlos A., Garcia, Gabriel J., Ubeda, Andres, Morell-Gimenez, Vicente, Gomez-Donoso, Francisco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Data Descriptor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008528/
https://www.ncbi.nlm.nih.gov/pubmed/36906700
http://dx.doi.org/10.1038/s41597-023-02031-3
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author Hernández, Óscar G.
Lopez-Castellanos, Jose M.
Jara, Carlos A.
Garcia, Gabriel J.
Ubeda, Andres
Morell-Gimenez, Vicente
Gomez-Donoso, Francisco
author_facet Hernández, Óscar G.
Lopez-Castellanos, Jose M.
Jara, Carlos A.
Garcia, Gabriel J.
Ubeda, Andres
Morell-Gimenez, Vicente
Gomez-Donoso, Francisco
author_sort Hernández, Óscar G.
collection PubMed
description Human Muscular Manipulability is a metric that measures the comfort of an specific pose and it can be used for a variety of applications related to healthcare. For this reason, we introduce KIMHu: a Kinematic, Imaging and electroMyography dataset for Human muscular manipulability index prediction. The dataset is comprised of images, depth maps, skeleton tracking data, electromyography recordings and 3 different Human Muscular Manipulability indexes of 20 participants performing different physical exercises with their arm. The methodology followed to acquire and process the data is also presented for future replication. A specific analysis framework for Human Muscular Manipulability is proposed in order to provide benchmarking tools based on this dataset.
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spelling pubmed-100085282023-03-13 A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction Hernández, Óscar G. Lopez-Castellanos, Jose M. Jara, Carlos A. Garcia, Gabriel J. Ubeda, Andres Morell-Gimenez, Vicente Gomez-Donoso, Francisco Sci Data Data Descriptor Human Muscular Manipulability is a metric that measures the comfort of an specific pose and it can be used for a variety of applications related to healthcare. For this reason, we introduce KIMHu: a Kinematic, Imaging and electroMyography dataset for Human muscular manipulability index prediction. The dataset is comprised of images, depth maps, skeleton tracking data, electromyography recordings and 3 different Human Muscular Manipulability indexes of 20 participants performing different physical exercises with their arm. The methodology followed to acquire and process the data is also presented for future replication. A specific analysis framework for Human Muscular Manipulability is proposed in order to provide benchmarking tools based on this dataset. Nature Publishing Group UK 2023-03-11 /pmc/articles/PMC10008528/ /pubmed/36906700 http://dx.doi.org/10.1038/s41597-023-02031-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Hernández, Óscar G.
Lopez-Castellanos, Jose M.
Jara, Carlos A.
Garcia, Gabriel J.
Ubeda, Andres
Morell-Gimenez, Vicente
Gomez-Donoso, Francisco
A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction
title A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction
title_full A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction
title_fullStr A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction
title_full_unstemmed A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction
title_short A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction
title_sort kinematic, imaging and electromyography dataset for human muscular manipulability index prediction
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008528/
https://www.ncbi.nlm.nih.gov/pubmed/36906700
http://dx.doi.org/10.1038/s41597-023-02031-3
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