Publication
Title
STAPP : spatiotemporal analysis of plantar pressure measurements using statistical parametric mapping
Author
Abstract
Background: Pedobarography produces large sets of plantar pressure samples that are routinely subsampled (e.g. using regions of interest) or aggregated (e.g. center of pressure trajectories, peak pressure images) in order to simplify statistical analysis and provide intuitive clinical measures. Research question: We hypothesize that these data reductions discard gait information that can be used to differentiate between groups or conditions. Methods: To test the hypothesis of null information loss, we created an implementation of statistical parametric mapping (SPM) for dynamic plantar pressure datasets (i.e. plantar pressure videos). Our SPM software framework brings all plantar pressure videos into anatomical and temporal correspondence, then performs statistical tests at each sampling location in space and time. Novelly, we introduce non-linear temporal registration into the framework in order to normalize for timing differences within the stance phase. We refer to our software framework as STAPP: spatiotemporal analysis of plantar pressure measurements. Using STAPP, we tested our hypothesis on plantar pressure videos from 33 healthy subjects walking at different speeds. Results: As walking speed increased, STAPP was able to identify significant decreases in plantar pressure at midstance from the heel through the lateral forefoot. The extent of these plantar pressure decreases has not previously been observed using existing plantar pressure analysis techniques. Significance: We therefore conclude that the subsampling of plantar pressure videos - a task which led to the discarding of gait information in our study - can be avoided using STAPP.
Language
English
Source (journal)
Gait and posture. - Oxford
Publication
Oxford : 2018
ISSN
0966-6362
Volume/pages
63 (2018) , p. 268-275
ISI
000435225300044
Pubmed ID
29793187
Full text (Publisher's DOI)
Full text (open access)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Project info
CAD WALK: Enabling Computer Aided Diagnosis of Foot Pathologies through the use of Metric Learning
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 02.08.2018
Last edited 20.09.2021
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