Cargando…

Dataset of lower extremity joint angles, moments and forces in distance running

This study presents a database of joint angles, moments, and forces of the lower extremity from distance running at a submaximal speed in recreational runners. Twenty recreational runners participated in two experimental sessions, specifically pre and post a 5k treadmill run, with a synchronous coll...

Descripción completa

Detalles Bibliográficos
Autores principales: Mei, Qichang, Fernandez, Justin, Xiang, Liangliang, Gao, Zixiang, Yu, Peimin, Baker, Julien S., Gu, Yaodong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9668536/
https://www.ncbi.nlm.nih.gov/pubmed/36406689
http://dx.doi.org/10.1016/j.heliyon.2022.e11517
_version_ 1784831935079514112
author Mei, Qichang
Fernandez, Justin
Xiang, Liangliang
Gao, Zixiang
Yu, Peimin
Baker, Julien S.
Gu, Yaodong
author_facet Mei, Qichang
Fernandez, Justin
Xiang, Liangliang
Gao, Zixiang
Yu, Peimin
Baker, Julien S.
Gu, Yaodong
author_sort Mei, Qichang
collection PubMed
description This study presents a database of joint angles, moments, and forces of the lower extremity from distance running at a submaximal speed in recreational runners. Twenty recreational runners participated in two experimental sessions, specifically pre and post a 5k treadmill run, with a synchronous collection of markers trajectories and ground reaction forces for both limbs in walking and running trials. The raw data in C3D files could be used for musculoskeletal modelling. Extra datasets of joint angles, moments, and forces are presented ready-for-use in MAT files, which could be as reference for study of biomechanical alterations from distance running. Applying advanced data processing techniques (Machine Learning algorithms) to these datasets (C3D&MAT), such as Principal Component Analysis, could extract key features of variation, thus potentially being applied for correlation with accelerometric and gyroscope parameters from wearable sensors during field running. Dataset of multi-segmental foot could be another contribution for the investigation of foot complex biomechanics from distance running. The dataset from Asian males may also be used for population-based studies of running biomechanics.
format Online
Article
Text
id pubmed-9668536
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-96685362022-11-17 Dataset of lower extremity joint angles, moments and forces in distance running Mei, Qichang Fernandez, Justin Xiang, Liangliang Gao, Zixiang Yu, Peimin Baker, Julien S. Gu, Yaodong Heliyon Research Article This study presents a database of joint angles, moments, and forces of the lower extremity from distance running at a submaximal speed in recreational runners. Twenty recreational runners participated in two experimental sessions, specifically pre and post a 5k treadmill run, with a synchronous collection of markers trajectories and ground reaction forces for both limbs in walking and running trials. The raw data in C3D files could be used for musculoskeletal modelling. Extra datasets of joint angles, moments, and forces are presented ready-for-use in MAT files, which could be as reference for study of biomechanical alterations from distance running. Applying advanced data processing techniques (Machine Learning algorithms) to these datasets (C3D&MAT), such as Principal Component Analysis, could extract key features of variation, thus potentially being applied for correlation with accelerometric and gyroscope parameters from wearable sensors during field running. Dataset of multi-segmental foot could be another contribution for the investigation of foot complex biomechanics from distance running. The dataset from Asian males may also be used for population-based studies of running biomechanics. Elsevier 2022-11-14 /pmc/articles/PMC9668536/ /pubmed/36406689 http://dx.doi.org/10.1016/j.heliyon.2022.e11517 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Mei, Qichang
Fernandez, Justin
Xiang, Liangliang
Gao, Zixiang
Yu, Peimin
Baker, Julien S.
Gu, Yaodong
Dataset of lower extremity joint angles, moments and forces in distance running
title Dataset of lower extremity joint angles, moments and forces in distance running
title_full Dataset of lower extremity joint angles, moments and forces in distance running
title_fullStr Dataset of lower extremity joint angles, moments and forces in distance running
title_full_unstemmed Dataset of lower extremity joint angles, moments and forces in distance running
title_short Dataset of lower extremity joint angles, moments and forces in distance running
title_sort dataset of lower extremity joint angles, moments and forces in distance running
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9668536/
https://www.ncbi.nlm.nih.gov/pubmed/36406689
http://dx.doi.org/10.1016/j.heliyon.2022.e11517
work_keys_str_mv AT meiqichang datasetoflowerextremityjointanglesmomentsandforcesindistancerunning
AT fernandezjustin datasetoflowerextremityjointanglesmomentsandforcesindistancerunning
AT xiangliangliang datasetoflowerextremityjointanglesmomentsandforcesindistancerunning
AT gaozixiang datasetoflowerextremityjointanglesmomentsandforcesindistancerunning
AT yupeimin datasetoflowerextremityjointanglesmomentsandforcesindistancerunning
AT bakerjuliens datasetoflowerextremityjointanglesmomentsandforcesindistancerunning
AT guyaodong datasetoflowerextremityjointanglesmomentsandforcesindistancerunning