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Abstract: Image registration, the process of optimally aligning homologous structures in multiple images, has recently been demonstrated to support automated pixel-level analysis of pedobarographic images and, subsequently, to extract unique and biomechanically relevant information from plantar pressure data. Recent registration methods have focused on robustness, with slow but globally powerful algorithms. In this paper, we present an alternative registration approach that affords both speed and accuracy, with the goal of making pedobarographic image registration more practical for near-real-time laboratory and clinical applications. The current algorithm first extracts centroid-based curvature trajectories from pressure image contours, and then optimally matches these curvature profiles using optimization based on dynamic programming. Special cases of disconnected images (that occur in high-arched subjects, for example) are dealt with by introducing an artificial spatially linear bridge between adjacent image clusters. Two registration algorithms were developed: a ‘geometric’ algorithm, which exclusively matched geometry, and a ‘hybrid’ algorithm, which performed subsequent pseudo-optimization. After testing the two algorithms on 30 control image pairs considered in a previous study, we found that, when compared with previously published results, the hybrid algorithm improved overlap ratio (p=0.010), but both current algorithms had slightly higher mean-squared error, assumedly because they did not consider pixel intensity. Nonetheless, both algorithms greatly improved the computational efficiency (25±8 and 53±9ms per image pair for geometric and hybrid registrations, respectively). These results imply that registration-based pixel-level pressure image analyses can, eventually, be implemented for practical clinical purposes. [Copyright &y& Elsevier]

Abstract: The height of the medial longitudinal arch (MLA) is thought to be a predisposing factor to various lower extremity injuries. Discrepancy exists as to whether MLA height plays a role in injury prevention. The purpose of this study was to determine the intertester and intratester reliability, and the validity of the mirrored foot photo box (MFPB) and caliper measurements to radiographic measurements. Methods: Thirty subjects with equal numbers of men and women were recruited. Both feet were tested (n=60) in a 90% weight bearing stance. A set of anatomic landmarks were palpated, marked, and measured using a caliper, MFPB, and radiographs. The protocol was completed by two testers on 2 days approximately 1 week apart. Intertester and intratester reliability were determined using the intraclass correlation coefficient (ICC)(2, k) and the ICC(2,1), respectively. Validity of both measurement techniques to radiographic measurements was determined using the ICC(2, k). Results: The intertester reliability ranged from 0.991 to 0.577, while the intratester reliability ranged from 0.994 to 0.527, with first metatarsal angle being the only variable with poor reliability. Most variables demonstrated acceptable validity between the MFPB and the caliper measurements, and acceptable validity between the MFPB and calipers compared to radiographic measurements. The MFPB took 51.3±19.6s per foot while the caliper measurements averaged 227.4±68.9s to complete the measurements. Discussion: The MFPB is as reliable as the caliper measurements, and offers better intertester reliability. Both the caliper and MFPB measurements demonstrated acceptable validity to radiographic measurements and testing time was reduced when using the MFPB compared to calipers. [Copyright &y& Elsevier]

A detailed understanding of foot morphology can enable the design of more comfortable and better fitting footwear. However, foot morphology varies widely within the population, and changes dynamically as the foot is loaded during stance. This study presents a parametric statistical shape model from 4D foot scans to capture both the inter- and intra-individual variability in foot morphology. Thirty subjects walked on a treadmill while 4D scans of their right foot were taken at 90 frames-per second during stance phase. Each subject's height, weight, foot length, foot width, arch length, and sex were also recorded. The 4D scans were all registered to a common high-quality foot scan, and a principal component analysis was done on all processed 4D scans. Elastic-net linear regression models were built to predict the principal component scores, which were then inverse transformed into 4D scans. The best performing model was selected with leave-one-out cross-validation. The chosen model predicts foot morphology across stance phase with a root-mean-square error of 5.2 ± 2.0 mm and a mean Hausdorff distance of 25.5 ± 13.4 mm. This study shows that statistical shape modeling can be used to predict dynamic changes in foot morphology across the population. The model can be used to investigate and improve foot-footwear interaction, allowing for better fitting and more comfortable footwear. [ABSTRACT FROM AUTHOR]

The unique shape of modern human feet, and how they change shape when loaded are thought to be integral to effective upright gait. This unique shape, and the natural variations therein, have previously been analysed using a range of methods; from visual assessments, anthropometric measurements, and footprints, to x-ray, ultrasound and magnetic resonance images. However, these methods are often limited by their use of linear two-dimensional measures. Only recently have advances in three-dimensional (3D) scanning technology and statistical shape analysis been applied to studying 3D foot shape variations. Given their novelty, information regarding the reliability and repeatability of 3D foot scanning and shape modelling is lacking. To investigate whether repeated foot scans captured by two examiners give the same 3D shape and produce consistent statistical shape models, 17 healthy adults' left feet were scanned while bearing half and full bodyweight, as well as minimal weight. Surface to surface distances between corresponding foot meshes and differences between shape model quality criteria were both found to be small and insignificant. The only exception being the specificity criterion for minimally loaded foot scans. Furthermore, Euclidean vectors were used to model the magnitude and direction of deformation that feet undergo as a consequence of increased loading. The deformation models showed that loading a minimally loaded foot results in greater, but less consistent, shape changes than when increasing the load on an already loaded foot. These results show that the utilized methods offer a valuable, reliable and repeatable approach to analysing foot shape and deformation. [ABSTRACT FROM AUTHOR]