Research Data Leeds Repository

STrain Analysis and Mapping of the Plantar Surface (STAMPS) – A novel technique of plantar load analysis during gait - Dataset.

Crossland, Sarah R. and Jones, Alexander D. and Nixon, Jane E. and Siddle, Heidi J. and Russell, David A. and Culmer, Peter R. (2023) STrain Analysis and Mapping of the Plantar Surface (STAMPS) – A novel technique of plantar load analysis during gait - Dataset. University of Leeds. [Dataset] https://doi.org/10.5518/1310

This item is part of the Tribology of the Plantar Aspect in Relation to Diabetic Ulceration collection.

Dataset description

This data set contains the collated regional strain and peak plantar pressure (PPP) data for the plantar aspect of the foot for participants 1-3 from the journal article "STrain Analysis and Mapping of the Plantar Surface (STAMPS) - A novel technique of plantar load analysis during gait".

Additional information: This dataset is not publicly available. Click the link under ‘Related resources’ to request access via the RADAR Restricted Access Data Repository. You will be asked to complete a request form explaining why you need access to the data. You will receive an initial response to your request within 5 working days.
Keywords: diabetes, shear, strain, plantar, digital image correlation
Divisions: Faculty of Engineering and Physical Sciences > School of Mechanical Engineering
Faculty of Medicine and Health > School of Medicine
Faculty of Medicine and Health > School of Medicine > Leeds Institute of Clinical Trials Research (LICTR)
Faculty of Medicine and Health > School of Medicine > Leeds Institute of Health Sciences (LIHS)
Faculty of Medicine and Health > School of Medicine > Leeds Institute of Rheumatic & Musculoskeletal Medicine (LIRMM)
Related resources:
LocationType
https://doi.org/10.1101/2023.03.10.23287086Publication
https://doi.org/10.1177/09544119231181797Publication
https://radar.researchdata.leeds.ac.uk/37/Dataset
License: Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited: 21 Apr 2023 17:06
URI: https://archive.researchdata.leeds.ac.uk/id/eprint/1093

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