Full Body Kinematics and Ground Reaction Forces of Fifty Heterogeneous Runners Completing Treadmill Running at Various Speeds and Gradients

This dataset includes 3-dimensional ground reaction force data (1000 Hz) collected from a gradient adjustable split belt Bertec instrumented treadmill (ITC-21-20) during running at a range of speeds and gradients. Alongside the ground reaction forces are marker based motion capture data. A full body markerset was tracked (250 Hz) using 12 Qualisys Miqus cameras and Qualisys Track Manager 2022, with additional anatomical markers tracked only during the static trial. Data was also collected from six inertial measurement unit sensors (Delsys Trigno) at 519 Hz, the sensors were secured to the following locations using either tape or Velcro strapping: medial left tibia, lateral left thigh, sacrum, T10 vertebrae, lateral left upperarm, and left wrist. All of this data was collected synchronously and saved to the typical motion capture format of c3d files. Fifty runners with mixed levels of experience and fitness levels are included in this dataset (25 males, 25 females).

Keywords:
Biomechanics, Running, Treadmill, Kinetics, Kinematics, Motion Capture, Wearables, Ground Reaction Forces
Subjects:
Medical and health interface

Cite this dataset as:
Carter, J., Chen, X., Cazzola, D., Trewartha, G., Preatoni, E., 2024. Full Body Kinematics and Ground Reaction Forces of Fifty Heterogeneous Runners Completing Treadmill Running at Various Speeds and Gradients. Bath: University of Bath Research Data Archive. Available from: https://doi.org/10.15125/BATH-01341.

Export

[QR code for this page]

Data

P002.zip
application/zip (568MB)
Creative Commons: Attribution 4.0

P003.zip
application/zip (597MB)
Creative Commons: Attribution 4.0

P004.zip
application/zip (592MB)
Creative Commons: Attribution 4.0

P006.zip
application/zip (572MB)
Creative Commons: Attribution 4.0

P007.zip
application/zip (587MB)
Creative Commons: Attribution 4.0

P008.zip
application/zip (529MB)
Creative Commons: Attribution 4.0

P009.zip
application/zip (597MB)
Creative Commons: Attribution 4.0

P010.zip
application/zip (612MB)
Creative Commons: Attribution 4.0

P011.zip
application/zip (587MB)
Creative Commons: Attribution 4.0

P012.zip
application/zip (609MB)
Creative Commons: Attribution 4.0

P013.zip
application/zip (608MB)
Creative Commons: Attribution 4.0

P014.zip
application/zip (569MB)
Creative Commons: Attribution 4.0

P015.zip
application/zip (598MB)
Creative Commons: Attribution 4.0

P016.zip
application/zip (610MB)
Creative Commons: Attribution 4.0

P017.zip
application/zip (609MB)
Creative Commons: Attribution 4.0

P018.zip
application/zip (580MB)
Creative Commons: Attribution 4.0

P019.zip
application/zip (566MB)
Creative Commons: Attribution 4.0

P020.zip
application/zip (598MB)
Creative Commons: Attribution 4.0

P021.zip
application/zip (593MB)
Creative Commons: Attribution 4.0

P022.zip
application/zip (586MB)
Creative Commons: Attribution 4.0

P023.zip
application/zip (589MB)
Creative Commons: Attribution 4.0

P024.zip
application/zip (569MB)
Creative Commons: Attribution 4.0

P025.zip
application/zip (459MB)
Creative Commons: Attribution 4.0

P026.zip
application/zip (592MB)
Creative Commons: Attribution 4.0

P027.zip
application/zip (536MB)
Creative Commons: Attribution 4.0

P029.zip
application/zip (603MB)
Creative Commons: Attribution 4.0

P028.zip
application/zip (593MB)
Creative Commons: Attribution 4.0

P030.zip
application/zip (587MB)
Creative Commons: Attribution 4.0

P032.zip
application/zip (544MB)
Creative Commons: Attribution 4.0

P033.zip
application/zip (528MB)
Creative Commons: Attribution 4.0

P031.zip
application/zip (594MB)
Creative Commons: Attribution 4.0

P034.zip
application/zip (581MB)
Creative Commons: Attribution 4.0

P035.zip
application/zip (596MB)
Creative Commons: Attribution 4.0

P036.zip
application/zip (555MB)
Creative Commons: Attribution 4.0

P037.zip
application/zip (534MB)
Creative Commons: Attribution 4.0

P038.zip
application/zip (583MB)
Creative Commons: Attribution 4.0

P039.zip
application/zip (592MB)
Creative Commons: Attribution 4.0

P040.zip
application/zip (599MB)
Creative Commons: Attribution 4.0

P042.zip
application/zip (599MB)
Creative Commons: Attribution 4.0

P041.zip
application/zip (586MB)
Creative Commons: Attribution 4.0

P045.zip
application/zip (599MB)
Creative Commons: Attribution 4.0

P043.zip
application/zip (571MB)
Creative Commons: Attribution 4.0

P044.zip
application/zip (512MB)
Creative Commons: Attribution 4.0

P046.zip
application/zip (599MB)
Creative Commons: Attribution 4.0

P047.zip
application/zip (571MB)
Creative Commons: Attribution 4.0

P049.zip
application/zip (538MB)
Creative Commons: Attribution 4.0

P050.zip
application/zip (585MB)
Creative Commons: Attribution 4.0

P051.zip
application/zip (558MB)
Creative Commons: Attribution 4.0

P052.zip
application/zip (601MB)
Creative Commons: Attribution 4.0

P048.zip
application/zip (562MB)
Creative Commons: Attribution 4.0

Participant_Info.csv
application/csv (1kB)
Creative Commons: Attribution 4.0

Creators

Josh Carter
Data Collector
University of Bath

Xi Chen
Supervisor
University of Bath

Dario Cazzola
Supervisor
University of Bath

Grant Trewartha
Supervisor
Teesside University

Ezio Preatoni
Project Leader
University of Bath

Contributors

University of Bath
Sponsor

NURVV
Sponsor

Documentation

Data collection method:

Full body kinematics were collected using a 12 camera Qualisys Miqus system (250 Hz), recordings for each trial were automated using a PAF project within Qualisys Track Manager 2022 software. Retroreflective marker locations are detailed within the 'MarkerSet_Info' document included in this dataset. All markers were secured with double sided tape and the clusters were also secured with medical bandages. Additional markers were used within a static trial, for the purpose of model scaling, prior to the start of the dynamic trials. Synchronised with the start of the motion capture recordings was the collection of three-dimensional ground reaction force data (1000 Hz) and inertial measurement unit data (519 Hz). The ground reaction force data was collected from a Bertec instrumented split belt treadmill (ITC-21-20), during the walking trials participants were instructed to walk across the two parallel belts with their left foot landing on force plate 1 and their right foot landing on force plate 2. During the running trials participants ran only on force plate 1 (left). The inertial measurement unit sensors used were the Delsys Trigno, collecting data through the Qualisys Track Manager API. The location of the sensors were based on common sensor locations within commercial wearable products. This included: medial left tibia, lateral left thigh, sacrum, T10 vertebrae, lateral left upperarm, and left wrist. The sensors were secured with a combination of double sided tape, adhesive spray, and velcro strapping depending on the location. Participants were recruited from local running clubs and via word of mouth. The aim during recruitment was to make the sample as heterogeneous as possible, with a wide range of ages and abilities included. The final sample also included 25 biological males and 25 biological females. Before the start of data collection participants were asked for the typical pace that they would complete a 30+ minute easy run at. This then set the baseline for the other speeds that data was collected at during their participation. Full information about the speeds and gradients of each trial can be calculated through the information provided in the 'FileNaming_Convention' file and the data in the 'Participant_Info' file. The protocol consisted of walking as well as running during 'flat', uphill, and downhill conditions. Participants were provided breaks between trials and offered to opportunity to take as many breaks between trials as required, the aim was to minimise the influence of fatigue on individuals technique, whilst collecting a variety of running conditions.

Data processing and preparation activities:

The only processing completed on this dataset was the labeling of marker trajectories within Qualisys Track Manager 2022. This labeling was completed to the best of our ability. However, due to obscured markers, poor marker tracking, or markers falling off the participant, every trial could not be perfectly labeled for the full length of the recording. It must also be noted that for some participants certain inertial measurement unit sensors fell off of the participant in later trials. As well as this, dropped samples within the delsys trigno sensors are seen, with certain participants' data heavily influenced by this. It is therefore advised if aiming to use the inertial measurement unit data within this dataset it is completed with caution and thorough gap filling and data screening is completed.

Documentation Files

FileNaming_Convention.txt
text/plain (915B)
Creative Commons: Attribution 4.0

MarkerSet_Info.docx
application/vnd.openxmlformats-officedocument.wordprocessingml.document (232kB)
Creative Commons: Attribution 4.0

Funders

NURVV

Research Studentship Award

Publication details

Publication date: 30 May 2024
by: University of Bath

Version: 1

DOI: https://doi.org/10.15125/BATH-01341

URL for this record: https://researchdata.bath.ac.uk/id/eprint/1341

Contact information

Please contact the Research Data Service in the first instance for all matters concerning this item.

Contact person: Josh Carter

Departments:

Faculty of Humanities & Social Sciences
Health