3D motion analysis dataset of healthy young adult volunteers walking and running on overground and treadmill

3D motion analysis dataset of healthy young adult volunteers walking and running on overground and treadmill

Used on clinical and sportive context, three-dimensional motion analysis is considered as the gold standard in the biomechanics field. The proposed dataset has been established on 30 asymptomatic young participants. Volunteers were asked to walk at slow, comfortable and fast speeds, and to run at comfortable and fast speeds on overground and treadmill using shoes. Three dimensional trajectories of 63 reflective markers, 3D ground reaction forces and moments were simultaneously recorded. A total of 4840 and 18159 gait cycles were measured for overground and treadmill walking, respectively. Additionally, 2931 and 18945 cycles were measured for overground and treadmill running, respectively. The dataset is presented in C3D and CSV files either in raw or pre-processed format. The aim of this dataset is to provide a complete set of data that will help for the gait characterization during clinical gait analysis and in a sportive context. This data could be used for the creation of a baseline database for clinical purposes to research activities exploring the gait and the run.

Trial files are referenced in the dataset in hierarchical folders ID/Session/Trial/Speed/Data/Files.extention with:
- ID (Folder): unique identifier for the volunteer
- Session (Folder): the session (Session1 or Session2)
- Trial (Folder): overground walking (Overground_Walk), treadmill walking (Treadmill_Walk), overground running (Overground_Run), treadmill running (Treadmill_Run) or Static record (Calibration)
- Speed (Folder): Slow, Comfortable, and Fast (for walk) or, Comfortable and Fast (for run)
- Data (Folder): post-process c3d/CSV file (Post_Process), raw c3d/CSV file (Raw) or videoshow compressed AVI files (Video).

Anthropometric and demographic parameters of each participant are stored in the metadata of the related post-process c3d/CSV files and in Excel file.

A custom Python code used to read data is freely available on the dataset (Python Folder).