Pedobarographic Statistical Parametric Mapping of plantar pressure data in new and confident walking infants: A preliminary analysis

Abstract

In infancy, plantar pressure data during walking has been investigated through regional approaches, whilst the use pedobarographic Statistical Parametric Mapping (pSPM) has not been reported. Analysis of pressure data using pSPM is higher in resolution and can enhance understanding of foot function development, providing novel insights into plantar pressure changes. This work aims to detail the implementation of the pSPM data processing framework on infants' pressure data, comparing plantar pressure patterns between new and confident walking steps. Twelve infants walked across an EMED- xl platform. Steps were extracted and imported into MATLAB for analysis. Maximum pressure pictures were transformed to point clouds and registered within and between participants with iterative closest point and coherent point drift algorithms, respectively. Root mean square error (RMSE) was calculated within both registrations as a quality measure. Pressure patterns were compared between new and confident walking using nonparametric-paired sample SPM1D t-test. RMSEs were under 1 mm for both registration algorithms. In the transition to confident walking, significantly increasing pressure was detected in the left central forefoot. Implementing pSPM to infants' pressure data was non-trivial, as several phases of data processing were required to ensure a robust approach. Our analysis highlighted the presence of significant changes in pressure in central left forefoot after 2.2 months of walking, which have not been reported before. This can be explained as previous regional approaches in infancy considered the forefoot as whole, preventing detection of changes in discrete anatomical regions.