Open Kinematic Dataset of Walking at Different Speeds in Type 2 Diabetes and Control Participants
收藏DataCite Commons2025-09-29 更新2026-01-12 收录
下载链接：
https://redata.anii.org.uy/citation?persistentId=doi:10.60895/redata/SB0OXW
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资源简介：
<p>The dataset includes kinematics data recorded by a Motion Capture System (Vicon Motion System, Oxford, UK) at 100Hz. Data were filtered (fourth-order zero-lag Butterworth low-pass filter with a cutoff frequency of 6 Hz) and exported with Vicon’s Nexus 2.15 software.</p>
<p><b> 📁 DM2_kinematics_data (JSON Dataset)</b></p>
<p><b> 📁 CG_kinematics_data (JSON Dataset)</b></p>
<p>These datasets contain walking trials data collected across 37 subjects: 15 with type 2 diabetes mellitus (DM2) and 22 healthy participants (CG). The groups were paired for age and sex. Each participant performed 5 sessions on a treadmill at different constant speeds: the individual's self-selected walking speed (SSWS), two speeds above and two speeds below the SSWS. During each session, up to three 30-second trials were recorded by the MOCAP system. The data is stored as a hierarchical JSON file for ease of parsing, analysis, and expansion.</p>
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<p><b>📐 Structure</b></p>
<p>The data is organized in four hierarchical levels:</p>
<p>Subject ID → Speed → Trial Number → Kinematic Variables (markers 3D position)</p>
<p>Where:</p>
<p>-- **Subject ID**: A numeric string (e.g., `"7"`), - **Speed**: Integer string representing the gait speedin hm/h (e.g., `"18"` means 1.8 km/h). Speed values can be easily converted to m/s by dividing for 36 (e.g. 18/36 = 0.5 m/s). - **Trial Number**: A string ID for each 30-second trial (e.g., `"1"`, `"2"`, etc.)</p>
<p>-Each trial entry contains a dictionary of 56 sampled variables over time: Frame and Subframe are index vars - The following variables are grouped by three, and named as right or left (R, L) + the name of the body marker + the axis (e.g. RLOBx, RLOBy, RLOBz, for a total of 9 anatomical positions and 18 markers). LOB = Temporal lobe; SH = Acromion; ELB = Elbow; WR = Ulnar stiloyd process; GT = Great Trochanter; KN = Knee (lateral); AN = Malleolus lateral; HEE = Heel; MT = 5th Metatarsal. The 3D space was calibrated following the right hand rule, with the axis "X" = mediolateral; "Y" = anteroposterior; "Z" = vertical. Values are in mm.</p>
<p><b> 📁 Subjects_groups_db (CSV File)</b></p>
<p>This table contains the participants' data</p>
---
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<p><b>🔎 Example </b></p>
<pre><code>{
{
"7": {
"45": {
"1": {
"Frame": [1, 2, 3, ...],
"Subframe": [0, 0, 0, ...],
"RLOBx": [61.44, 61.92, 60.88, ...],
"RLOBy": [56.09, 56.09, 54.58, ...],
...
}
}
}
}</code></pre>
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</html>
本数据集包含由运动捕捉系统（Motion Capture System，英国牛津Vicon运动捕捉系统）以100Hz采样率记录的运动学数据。数据经四阶零延迟巴特沃斯低通滤波器（fourth-order zero-lag Butterworth low-pass filter，截止频率6Hz）滤波处理，并通过Vicon的Nexus 2.15软件导出。
📁 DM2_kinematics_data（JSON数据集）
📁 CG_kinematics_data（JSON数据集）
上述数据集包含37名受试者的行走试次数据，其中15名为2型糖尿病（type 2 diabetes mellitus, DM2）患者，22名为健康对照（Control Group, CG）受试者。两组按年龄与性别进行匹配。每位受试者在跑台上完成5组不同恒定速度的行走测试：包含个体自主选择行走速度（self-selected walking speed, SSWS），以及该速度上下各2组的额外速度。每组测试中，运动捕捉系统（MOCAP）可记录最多3段时长30秒的行走试次。数据以层级化JSON格式存储，便于解析、分析与扩展。
---
📐 数据结构
本数据集采用四级层级结构组织：
受试者编号 → 行走速度 → 试次编号 → 运动学变量（标记点三维位置）
各层级含义如下：
- **受试者编号**：数字字符串（例如`"7"`）
- **行走速度**：以十分之一公里每小时为单位的整数字符串（例如`"18"`代表1.8 km/h）。速度值可通过除以36快速转换为米每秒（例如18/36=0.5 m/s）
- **试次编号**：每段30秒试次的字符串标识（例如`"1"`、`"2"`等）
每个试次条目包含一个包含56个时序采样变量的字典：其中Frame（帧号）与Subframe（子帧号）为索引变量。其余变量按每三个一组命名，格式为「左/右（R/L）+ 身体标记点名称 + 坐标轴方向」，例如RLOBx、RLOBy、RLOBz，共覆盖9个解剖部位、18个标记点。各缩写对应解剖部位如下：
LOB = 颞叶（Temporal lobe）；SH = 肩峰（Acromion）；ELB = 肘关节（Elbow）；WR = 尺骨茎突（Ulnar styloid process，原文存在拼写笔误"stiloyd"，已修正为"styloid"）；GT = 大转子（Great Trochanter）；KN = 外侧膝关节（Knee (lateral)）；AN = 外踝（Malleolus lateral）；HEE = 足跟（Heel）；MT = 第五跖骨（5th Metatarsal）。
三维空间采用右手定则校准：X轴为内外侧方向，Y轴为前后方向，Z轴为垂直方向，所有数值单位均为毫米（mm）。
📁 Subjects_groups_db（CSV文件）
该表格包含所有受试者的基础信息。
---
🔎 示例
json
{
"7": {
"45": {
"1": {
"Frame": [1, 2, 3, ...],
"Subframe": [0, 0, 0, ...],
"RLOBx": [61.44, 61.92, 60.88, ...],
"RLOBy": [56.09, 56.09, 54.58, ...],
...
}
}
}
}
提供机构：
Repositorio de datos abiertos de investigación de Uruguay
创建时间：
2025-09-07
