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DUO-GAIT: A gait dataset for walking under dual-task and fatigue conditions with inertial measurement units

In recent years, there has been a growing interest in developing and evaluating gait analysis algorithms based on inertial measurement unit (IMU) data, which has important implications, including sports, assessment of diseases, and rehabilitation. Multi-tasking and physical fatigue are two relevant...

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Autores principales: Zhou, Lin, Fischer, Eric, Brahms, Clemens Markus, Granacher, Urs, Arnrich, Bert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442385/
https://www.ncbi.nlm.nih.gov/pubmed/37604913
http://dx.doi.org/10.1038/s41597-023-02391-w
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author Zhou, Lin
Fischer, Eric
Brahms, Clemens Markus
Granacher, Urs
Arnrich, Bert
author_facet Zhou, Lin
Fischer, Eric
Brahms, Clemens Markus
Granacher, Urs
Arnrich, Bert
author_sort Zhou, Lin
collection PubMed
description In recent years, there has been a growing interest in developing and evaluating gait analysis algorithms based on inertial measurement unit (IMU) data, which has important implications, including sports, assessment of diseases, and rehabilitation. Multi-tasking and physical fatigue are two relevant aspects of daily life gait monitoring, but there is a lack of publicly available datasets to support the development and testing of methods using a mobile IMU setup. We present a dataset consisting of 6-minute walks under single- (only walking) and dual-task (walking while performing a cognitive task) conditions in unfatigued and fatigued states from sixteen healthy adults. Especially, nine IMUs were placed on the head, chest, lower back, wrists, legs, and feet to record under each of the above-mentioned conditions. The dataset also includes a rich set of spatio-temporal gait parameters that capture the aspects of pace, symmetry, and variability, as well as additional study-related information to support further analysis. This dataset can serve as a foundation for future research on gait monitoring in free-living environments.
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spelling pubmed-104423852023-08-23 DUO-GAIT: A gait dataset for walking under dual-task and fatigue conditions with inertial measurement units Zhou, Lin Fischer, Eric Brahms, Clemens Markus Granacher, Urs Arnrich, Bert Sci Data Data Descriptor In recent years, there has been a growing interest in developing and evaluating gait analysis algorithms based on inertial measurement unit (IMU) data, which has important implications, including sports, assessment of diseases, and rehabilitation. Multi-tasking and physical fatigue are two relevant aspects of daily life gait monitoring, but there is a lack of publicly available datasets to support the development and testing of methods using a mobile IMU setup. We present a dataset consisting of 6-minute walks under single- (only walking) and dual-task (walking while performing a cognitive task) conditions in unfatigued and fatigued states from sixteen healthy adults. Especially, nine IMUs were placed on the head, chest, lower back, wrists, legs, and feet to record under each of the above-mentioned conditions. The dataset also includes a rich set of spatio-temporal gait parameters that capture the aspects of pace, symmetry, and variability, as well as additional study-related information to support further analysis. This dataset can serve as a foundation for future research on gait monitoring in free-living environments. Nature Publishing Group UK 2023-08-21 /pmc/articles/PMC10442385/ /pubmed/37604913 http://dx.doi.org/10.1038/s41597-023-02391-w 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Zhou, Lin
Fischer, Eric
Brahms, Clemens Markus
Granacher, Urs
Arnrich, Bert
DUO-GAIT: A gait dataset for walking under dual-task and fatigue conditions with inertial measurement units
title DUO-GAIT: A gait dataset for walking under dual-task and fatigue conditions with inertial measurement units
title_full DUO-GAIT: A gait dataset for walking under dual-task and fatigue conditions with inertial measurement units
title_fullStr DUO-GAIT: A gait dataset for walking under dual-task and fatigue conditions with inertial measurement units
title_full_unstemmed DUO-GAIT: A gait dataset for walking under dual-task and fatigue conditions with inertial measurement units
title_short DUO-GAIT: A gait dataset for walking under dual-task and fatigue conditions with inertial measurement units
title_sort duo-gait: a gait dataset for walking under dual-task and fatigue conditions with inertial measurement units
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442385/
https://www.ncbi.nlm.nih.gov/pubmed/37604913
http://dx.doi.org/10.1038/s41597-023-02391-w
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