[2502.17244] A dataset of high-resolution plantar pressures for gait analysis across varying footwear and walking speeds

Computer Science > Computer Vision and Pattern Recognition arXiv:2502.17244 (cs) [Submitted on 24 Feb 2025 (v1), last revised 4 Mar 2026 (this version, v5)] Title:A dataset of high-resolution plantar pressures for gait analysis across varying footwear and walking speeds Authors:Robyn Larracy, Angkoon Phinyomark, Ala Salehi, Eve MacDonald, Saeed Kazemi, Shikder Shafiul Bashar, Aaron Tabor, Erik Scheme View a PDF of the paper titled A dataset of high-resolution plantar pressures for gait analysis across varying footwear and walking speeds, by Robyn Larracy and 7 other authors View PDF HTML (experimental) Abstract:Gait refers to the patterns of limb movement generated during walking, which are unique to each individual due to both physical and behavioral traits. Walking patterns have been widely studied in biometrics, biomechanics, sports, and rehabilitation. While traditional methods rely on video and motion capture, advances in plantar pressure sensing technology now offer deeper insights into gait. However, underfoot pressures during walking remain underexplored due to the lack of large, publicly accessible datasets. To address this, we introduce the UNB StepUP-P150 dataset: a footStep database for gait analysis and recognition using Underfoot Pressure, including data from 150 individuals. This dataset comprises high-resolution plantar pressure data (4 sensors per cm-squared) collected using a 1.2m by 3.6m pressure-sensing walkway. It contains over 200,000 footsteps from p...