Running Injury Clinic Kinematic Dataset

OverviewBiomechanics dataset of human subjects (N=1798) walking and or running on a treadmill. Data include 3D marker positions over trials ranging from 25-60 seconds. Also included are demographic information and calculated variables of interest (step with, stride rate, peak knee flexion angle, etc...), sample processing code, and data analysis tutorials.<br>This dataset accompanies an article with the following citation:Ferber R, Brett A, Fukuchi RK, Hettinga B, Osis ST. (2024). A Biomechanical Dataset of 1,798 Healthy and Injured Subjects During Treadmill Walking and Running. <i>Scientific Data - Nature</i>. 11:1232 | https://doi.org/10.1038/s41597-024-04011-7Data DescriptionContained within this dataset are 4 categories of files. They consist of datafiles (.JSON format -&gt;2506 files), metadata (.CSV format -&gt;2 files), Matlab processing code (.M, .MAT format -&gt; 8 files) and Matlab tutorial files (.M, .MLX, .MAT format -&gt; 8 files). All code which accompanies this dataset (processing and tutorials) can be found in the "supplementary_materials.zip" file.Data files are contained within the zipped folder "ric_data" which itself a contains series of folders with names representing the subject ID. Each subject ID folder contains timestamped datafile(s) in ".json" format with each containing walking and/or running data from a single collection session.MethodsThree-dimensional (3D) marker trajectory data were captured using either a 3-camera or an 8-camera VICON motion capture system (Bonita or MX3+, Vicon Motion Systems Oxford, UK) while participants walked or ran on a treadmill. Spherical retro-reflective markers were placed on anatomical landmarks and rigid plates with clusters of 3-4 markers were placed on each of seven lower body segments as per Pohl et al. (Gait Posture. 2010;32(4):559-563.). The marker-set consisted of seven rigid segments and followed International Society of Biomechanics standards. To allow for unobstructed movement during running, anatomical markers were removed following a one second static trial where subjects stood upon a template with their feet positioned straight ahead and 0.3m apart with arms crossed over their chest. Following a warmup period of 2-5mins, kinematic data were collected for approximately 60 seconds while participants walked and then ran at a self-selected speed.Data were collected at the University of Calgary Running Injury Clinic as part of research studies or as part of clinical practice between 2009 and 2017. All subjects provided informed consent and all data were collected under approval from the University of Calgary's Conjoint Health Research Ethics Board (CHREB) (Ethics IDs: E–21705, E–22194, E–24339). In total, n=1197 (67%) can be considered unique datasets and have not been published in previous scientific manuscripts. However, 33% of the dataset (n=601) were recruited for specific research studies and as such, have been used in previously published works including comparisons between recreational and competitive runners, healthy and knee osteoarthritis patients , developing novel methods for MoCap marker placement, and determination of subgroups in healthy and injured runners. Please see accompanying paper for references to these studies.More detailsMore details regarding this dataset can be found in the README file. This file contains more detailed descriptions of the contents of the datafiles, processing code, and tutorial code.LicensingThe data is protected under a CC BY 4.0 license. All scripts and functions are protected under a permissive MIT license which can be found in the file LICENSE.txt.数据集概览：本数据集包含1798名人类受试者在跑台行走或跑步时的生物力学数据。数据涵盖时长25至60秒的测试序列中的三维标记点位置信息，同时包含人口统计学资料、目标计算变量（如步宽、步频、膝关节屈曲峰值角度等）、示例处理代码以及数据分析教程。 本数据集配套发表于以下引文的学术论文：Ferber R、Brett A、Fukuchi RK、Hettinga B、Osis ST. (2024). 1798名健康与损伤受试者跑台行走及跑步的生物力学数据集. 《自然·科学数据》（Scientific Data - Nature），11:1232 | https://doi.org/10.1038/s41597-024-04011-7 数据说明：本数据集包含四类文件，分别为数据文件（JSON格式，共2506个）、元数据文件（CSV格式，共2个）、Matlab处理代码文件（.M、.MAT格式，共8个）以及Matlab教程文件（.M、.MLX、.MAT格式，共8个）。本数据集配套的所有代码（处理代码与教程代码）均可在"supplementary_materials.zip"压缩包中获取。 数据文件存储于"ric_data"压缩文件夹内，该文件夹下包含若干以受试者ID命名的子文件夹。每个受试者ID子文件夹内包含带时间戳的JSON格式数据文件，每个文件对应单次采集会话中的行走和/或跑步数据。 研究方法：采用3相机或8相机VICON运动捕捉系统（Bonita或MX3+型号，英国牛津Vicon Motion Systems公司）采集受试者在跑台行走或跑步时的三维（3D）标记点轨迹数据。按照Pohl等人（《步态与姿势》，2010；32(4):559-563）的方案，将球形反光标记点粘贴于解剖标志点，并在7个下肢节段分别安装带有3-4个标记点的刚性板。该标记点系统包含7个刚性节段，符合国际生物力学学会标准。为确保跑步时运动不受阻，先进行1秒的静态校准测试：受试者站立于校准模板上，双脚正向分开0.3米，双臂交叉于胸前，随后移除解剖标记点。经过2-5分钟的热身阶段后，采集受试者以自选速度行走及跑步时的运动学数据，时长约60秒。 本数据集于2009年至2017年间在卡尔加里大学跑步损伤诊所采集，部分数据作为研究项目或临床实践的一部分。所有受试者均签署知情同意书，数据采集工作均获得卡尔加里大学联合健康研究伦理委员会（CHREB）批准（伦理编号：E–21705、E–22194、E–24339）。其中共1197份（67%）为独有的未在既往学术论文中发表的数据集；剩余33%（n=601）为特定研究项目招募的受试者数据，已被用于既往发表的研究，包括休闲跑者与竞技跑者的对比、健康人群与膝骨关节炎患者的对比、运动捕捉（Motion Capture，MoCap）标记点放置新方法开发，以及健康与损伤跑者的亚组划分等。相关研究的参考文献详见配套论文。 更多详情：关于本数据集的更多说明可参阅README文件，该文件详细阐述了数据文件、处理代码及教程代码的具体内容。 授权许可：本数据集采用CC BY 4.0协议进行保护。所有脚本与函数采用宽松的MIT协议保护，详情可参见LICENSE.txt文件。