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A multi-sensor human gait dataset captured through an optical system and inertial measurement units
Different technologies can acquire data for gait analysis, such as optical systems and inertial measurement units (IMUs). Each technology has its drawbacks and advantages, fitting best to particular applications. The presented multi-sensor human gait dataset comprises synchronized inertial and optic...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9452504/ https://www.ncbi.nlm.nih.gov/pubmed/36071060 http://dx.doi.org/10.1038/s41597-022-01638-2 |
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author | Santos, Geise Wanderley, Marcelo Tavares, Tiago Rocha, Anderson |
author_facet | Santos, Geise Wanderley, Marcelo Tavares, Tiago Rocha, Anderson |
author_sort | Santos, Geise |
collection | PubMed |
description | Different technologies can acquire data for gait analysis, such as optical systems and inertial measurement units (IMUs). Each technology has its drawbacks and advantages, fitting best to particular applications. The presented multi-sensor human gait dataset comprises synchronized inertial and optical motion data from 25 participants free of lower-limb injuries, aged between 18 and 47 years. A smartphone and a custom micro-controlled device with an IMU were attached to one of the participant’s legs to capture accelerometer and gyroscope data, and 42 reflexive markers were taped over the whole body to record three-dimensional trajectories. The trajectories and inertial measurements were simultaneously recorded and synchronized. Participants were instructed to walk on a straight-level walkway at their normal pace. Ten trials for each participant were recorded and pre-processed in each of two sessions, performed on different days. This dataset supports the comparison of gait parameters and properties of inertial and optical capture systems, whereas allows the study of gait characteristics specific for each system. |
format | Online Article Text |
id | pubmed-9452504 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-94525042022-09-09 A multi-sensor human gait dataset captured through an optical system and inertial measurement units Santos, Geise Wanderley, Marcelo Tavares, Tiago Rocha, Anderson Sci Data Data Descriptor Different technologies can acquire data for gait analysis, such as optical systems and inertial measurement units (IMUs). Each technology has its drawbacks and advantages, fitting best to particular applications. The presented multi-sensor human gait dataset comprises synchronized inertial and optical motion data from 25 participants free of lower-limb injuries, aged between 18 and 47 years. A smartphone and a custom micro-controlled device with an IMU were attached to one of the participant’s legs to capture accelerometer and gyroscope data, and 42 reflexive markers were taped over the whole body to record three-dimensional trajectories. The trajectories and inertial measurements were simultaneously recorded and synchronized. Participants were instructed to walk on a straight-level walkway at their normal pace. Ten trials for each participant were recorded and pre-processed in each of two sessions, performed on different days. This dataset supports the comparison of gait parameters and properties of inertial and optical capture systems, whereas allows the study of gait characteristics specific for each system. Nature Publishing Group UK 2022-09-07 /pmc/articles/PMC9452504/ /pubmed/36071060 http://dx.doi.org/10.1038/s41597-022-01638-2 Text en © The Author(s) 2022 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 Santos, Geise Wanderley, Marcelo Tavares, Tiago Rocha, Anderson A multi-sensor human gait dataset captured through an optical system and inertial measurement units |
title | A multi-sensor human gait dataset captured through an optical system and inertial measurement units |
title_full | A multi-sensor human gait dataset captured through an optical system and inertial measurement units |
title_fullStr | A multi-sensor human gait dataset captured through an optical system and inertial measurement units |
title_full_unstemmed | A multi-sensor human gait dataset captured through an optical system and inertial measurement units |
title_short | A multi-sensor human gait dataset captured through an optical system and inertial measurement units |
title_sort | multi-sensor human gait dataset captured through an optical system and inertial measurement units |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9452504/ https://www.ncbi.nlm.nih.gov/pubmed/36071060 http://dx.doi.org/10.1038/s41597-022-01638-2 |
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