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A dataset of asymptomatic human gait and movements obtained from markers, IMUs, insoles and force plates
Human motion capture and analysis could be made easier through the use of wearable devices such as inertial sensors and/or pressure insoles. However, many steps are still needed to reach the performance of optoelectronic systems to compute kinematic parameters. The proposed dataset has been establis...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10063557/ https://www.ncbi.nlm.nih.gov/pubmed/36997555 http://dx.doi.org/10.1038/s41597-023-02077-3 |
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author | Grouvel, Gautier Carcreff, Lena Moissenet, Florent Armand, Stéphane |
author_facet | Grouvel, Gautier Carcreff, Lena Moissenet, Florent Armand, Stéphane |
author_sort | Grouvel, Gautier |
collection | PubMed |
description | Human motion capture and analysis could be made easier through the use of wearable devices such as inertial sensors and/or pressure insoles. However, many steps are still needed to reach the performance of optoelectronic systems to compute kinematic parameters. The proposed dataset has been established on 10 asymptomatic adults. Participants were asked to walk at different speeds on a 10-meters walkway in a laboratory and to perform different movements such as squats or knee flexion/extension tasks. Three-dimensional trajectories of 69 reflective markers placed according to a conventional full body markerset, acceleration and angular velocity signals of 8 inertial sensors, pressure signals of 2 insoles, 3D ground reaction forces and moments obtained from 3 force plates were simultaneously recorded. Eight calculated virtual markers related to joint centers were also added to the dataset. This dataset contains a total of 337 trials including static and dynamic tasks for each participant. Its purpose is to enable comparisons between various motion capture systems and stimulate the development of new methods for gait analysis. |
format | Online Article Text |
id | pubmed-10063557 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100635572023-04-01 A dataset of asymptomatic human gait and movements obtained from markers, IMUs, insoles and force plates Grouvel, Gautier Carcreff, Lena Moissenet, Florent Armand, Stéphane Sci Data Data Descriptor Human motion capture and analysis could be made easier through the use of wearable devices such as inertial sensors and/or pressure insoles. However, many steps are still needed to reach the performance of optoelectronic systems to compute kinematic parameters. The proposed dataset has been established on 10 asymptomatic adults. Participants were asked to walk at different speeds on a 10-meters walkway in a laboratory and to perform different movements such as squats or knee flexion/extension tasks. Three-dimensional trajectories of 69 reflective markers placed according to a conventional full body markerset, acceleration and angular velocity signals of 8 inertial sensors, pressure signals of 2 insoles, 3D ground reaction forces and moments obtained from 3 force plates were simultaneously recorded. Eight calculated virtual markers related to joint centers were also added to the dataset. This dataset contains a total of 337 trials including static and dynamic tasks for each participant. Its purpose is to enable comparisons between various motion capture systems and stimulate the development of new methods for gait analysis. Nature Publishing Group UK 2023-03-30 /pmc/articles/PMC10063557/ /pubmed/36997555 http://dx.doi.org/10.1038/s41597-023-02077-3 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 Grouvel, Gautier Carcreff, Lena Moissenet, Florent Armand, Stéphane A dataset of asymptomatic human gait and movements obtained from markers, IMUs, insoles and force plates |
title | A dataset of asymptomatic human gait and movements obtained from markers, IMUs, insoles and force plates |
title_full | A dataset of asymptomatic human gait and movements obtained from markers, IMUs, insoles and force plates |
title_fullStr | A dataset of asymptomatic human gait and movements obtained from markers, IMUs, insoles and force plates |
title_full_unstemmed | A dataset of asymptomatic human gait and movements obtained from markers, IMUs, insoles and force plates |
title_short | A dataset of asymptomatic human gait and movements obtained from markers, IMUs, insoles and force plates |
title_sort | dataset of asymptomatic human gait and movements obtained from markers, imus, insoles and force plates |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10063557/ https://www.ncbi.nlm.nih.gov/pubmed/36997555 http://dx.doi.org/10.1038/s41597-023-02077-3 |
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