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Dataset of 3D gait analysis in typically developing children walking at three different speeds on an instrumented treadmill in virtual reality
In this article, gait data of typically developing (TD) children (24 boys/31 girls, mean (95% confidence interval) age 9.38 (8.51 – 10.25) years, body mass 35.67 (31.40 – 39.94) kg, leg length 0.73 (0.70 – 0.76) m, and height 1.41 (1.35 – 1.46) m) walking at different walking speeds is shared public...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10126839/ https://www.ncbi.nlm.nih.gov/pubmed/37113500 http://dx.doi.org/10.1016/j.dib.2023.109142 |
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author | Senden, Rachel Marcellis, Rik Meijer, Kenneth Willems, Paul Lenssen, Ton Staal, Heleen Janssen, Yvonne Groen, Vincent Vermeulen, Roland Jeroen Witlox, Marianne |
author_facet | Senden, Rachel Marcellis, Rik Meijer, Kenneth Willems, Paul Lenssen, Ton Staal, Heleen Janssen, Yvonne Groen, Vincent Vermeulen, Roland Jeroen Witlox, Marianne |
author_sort | Senden, Rachel |
collection | PubMed |
description | In this article, gait data of typically developing (TD) children (24 boys/31 girls, mean (95% confidence interval) age 9.38 (8.51 – 10.25) years, body mass 35.67 (31.40 – 39.94) kg, leg length 0.73 (0.70 – 0.76) m, and height 1.41 (1.35 – 1.46) m) walking at different walking speeds is shared publicly. Raw and processed data is presented for each child separately and includes data of each single step of both legs. Beside, the subject demographics and the results from the physical examination are presented allowing to select TD children from the database to create a matched group, based on specific parameters (e.g. sex and body weight). For clinical application, gait data is also presented per age group, which provides quick insight into the normal gait pattern of TD children of varying age. Gait analysis was performed during treadmill walking in a virtual environment using the Computer Assisted Rehabilitation Environment (CAREN). The human body lower limb model with trunk markers (HBM2) was used as biomechanical model. Children walked at comfortable walking speed, 30% slower and 30% faster (random sequence) while wearing gymnastic shoes and a safety harness to prevent falling. For each speed condition, 250 steps were recorded. Data quality check, step detection and the calculation of gait parameters was done by custom made Matlab algorithms. Raw data files are provided per walking speed, for each child separately. The raw data is exported from the CAREN software (D-flow) and is provided in .mox and .txt files. It includes the output from the models such as subject data, marker and force data, kinematic data (joint angles), kinetic data (joint moments, GRFs, joint powers), as well as CoM data and EMG data (the last two are not described in this manuscript), for each speed condition and each child. Unfiltered and filtered data are included. C3D files with raw marker and GRF data were recorded in Nexus (Vicon software) and are available upon request. After analyzing the raw data into Matlab (R2016a, Mathworks) using custom made Matlab algorithms, processed data is obtained. The processed data is provided in .xls files and is also presented for each child separately. It contains spatiotemporal parameters, 3D joint angles, anterior-posterior and vertical ground reaction forces (GRF), 3D joint moments and sagittal joint power of each step of the left and right leg. In addition to each individual's data, overview files (.xls) are created per walking speed condition. These overviews present the averaged gait parameter (e.g. joint angle), calculated over all valid steps, of each child. |
format | Online Article Text |
id | pubmed-10126839 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-101268392023-04-26 Dataset of 3D gait analysis in typically developing children walking at three different speeds on an instrumented treadmill in virtual reality Senden, Rachel Marcellis, Rik Meijer, Kenneth Willems, Paul Lenssen, Ton Staal, Heleen Janssen, Yvonne Groen, Vincent Vermeulen, Roland Jeroen Witlox, Marianne Data Brief Data Article In this article, gait data of typically developing (TD) children (24 boys/31 girls, mean (95% confidence interval) age 9.38 (8.51 – 10.25) years, body mass 35.67 (31.40 – 39.94) kg, leg length 0.73 (0.70 – 0.76) m, and height 1.41 (1.35 – 1.46) m) walking at different walking speeds is shared publicly. Raw and processed data is presented for each child separately and includes data of each single step of both legs. Beside, the subject demographics and the results from the physical examination are presented allowing to select TD children from the database to create a matched group, based on specific parameters (e.g. sex and body weight). For clinical application, gait data is also presented per age group, which provides quick insight into the normal gait pattern of TD children of varying age. Gait analysis was performed during treadmill walking in a virtual environment using the Computer Assisted Rehabilitation Environment (CAREN). The human body lower limb model with trunk markers (HBM2) was used as biomechanical model. Children walked at comfortable walking speed, 30% slower and 30% faster (random sequence) while wearing gymnastic shoes and a safety harness to prevent falling. For each speed condition, 250 steps were recorded. Data quality check, step detection and the calculation of gait parameters was done by custom made Matlab algorithms. Raw data files are provided per walking speed, for each child separately. The raw data is exported from the CAREN software (D-flow) and is provided in .mox and .txt files. It includes the output from the models such as subject data, marker and force data, kinematic data (joint angles), kinetic data (joint moments, GRFs, joint powers), as well as CoM data and EMG data (the last two are not described in this manuscript), for each speed condition and each child. Unfiltered and filtered data are included. C3D files with raw marker and GRF data were recorded in Nexus (Vicon software) and are available upon request. After analyzing the raw data into Matlab (R2016a, Mathworks) using custom made Matlab algorithms, processed data is obtained. The processed data is provided in .xls files and is also presented for each child separately. It contains spatiotemporal parameters, 3D joint angles, anterior-posterior and vertical ground reaction forces (GRF), 3D joint moments and sagittal joint power of each step of the left and right leg. In addition to each individual's data, overview files (.xls) are created per walking speed condition. These overviews present the averaged gait parameter (e.g. joint angle), calculated over all valid steps, of each child. Elsevier 2023-04-12 /pmc/articles/PMC10126839/ /pubmed/37113500 http://dx.doi.org/10.1016/j.dib.2023.109142 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Senden, Rachel Marcellis, Rik Meijer, Kenneth Willems, Paul Lenssen, Ton Staal, Heleen Janssen, Yvonne Groen, Vincent Vermeulen, Roland Jeroen Witlox, Marianne Dataset of 3D gait analysis in typically developing children walking at three different speeds on an instrumented treadmill in virtual reality |
title | Dataset of 3D gait analysis in typically developing children walking at three different speeds on an instrumented treadmill in virtual reality |
title_full | Dataset of 3D gait analysis in typically developing children walking at three different speeds on an instrumented treadmill in virtual reality |
title_fullStr | Dataset of 3D gait analysis in typically developing children walking at three different speeds on an instrumented treadmill in virtual reality |
title_full_unstemmed | Dataset of 3D gait analysis in typically developing children walking at three different speeds on an instrumented treadmill in virtual reality |
title_short | Dataset of 3D gait analysis in typically developing children walking at three different speeds on an instrumented treadmill in virtual reality |
title_sort | dataset of 3d gait analysis in typically developing children walking at three different speeds on an instrumented treadmill in virtual reality |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10126839/ https://www.ncbi.nlm.nih.gov/pubmed/37113500 http://dx.doi.org/10.1016/j.dib.2023.109142 |
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