Abstract
Arch height is an important determinant for the risk of foot pathology, especially in an aging population. Current methods for analyzing footprints require substantial manual processing time. The current research investigated automated determination of foot type based on features derived from the Gabor wavelet utilizing digitized footprints to allow timely assessment of foot type and focused intervention. Two hundred and eighty footprints were collected, and area, perimeter, curvature, circularity, 2nd wavelet moment, mean bending energy (MBE), and entropy were determined using in house developed MATLAB codes. The results were compared to the gold standard using Spearman’s Correlation coefficient and multiple linear regression models with significance set at 0.05. The proposed approach found MBE combined with foot perimeter to give the best results as shown by ANOVA (F(2,211) = 10.18, p < 0.0001) with the mean ±SD of low, normal, and high arch being, respectively, 0.26 ± 0.025,.24 ± 0.021, and 0.23 ± 0.024. A clinical review of the new cut off values, as set by the first and the third quartiles of our sample, lead to reliability up to 87%. Our results suggest that automated wavelet-based foot type classification of 2D binary images of the plantar surface of the foot is comparable to current state-of-the-art methods providing a cost and time effective tool suitable for clinical diagnostics.
Highlights
The arch height of the foot has long been recognized as a key parameter in foot type classification, and is considered an important prediction and diagnostic tool in lower limb pathology
Ethics approval was granted from the Human Research Ethics Committee (HREC) at the University of Newcastle (Protocol Number 2012–0385) and all participants provided written consent following an information session Initially, the arch index proposed by C&R, representing the current gold standard method, was determined
Our model distinguished the classes proposed by Cavanagh and Rogers providing a reliable tool in determining foot type
Summary
The arch height of the foot has long been recognized as a key parameter in foot type classification, and is considered an important prediction and diagnostic tool in lower limb pathology. Several non-invasive methods based on footprint images have been proposed as useful measures in gait and movement analysis (Johnston, 2014) These methods require extensive processing, are very time consuming and largely underutilized by clinicians and researchers. Medial longitudinal arch height is important in shock absorption, providing support while walking (Ghasemi et al, 2016) Abnormal arch height such as high arches, flat feet or fallen arches (Figure 2) can be responsible for discomfort and more serious pathology, such as, lumbar lordosis, foot eversion, and knees injuries (Nigg et al, 1993), plantar fasciitis, tibialis posterior tendon dysfunction (Johnson and Strom, 1989; Schepsis et al, 1991). The methodology is based on features derived from geometrical characteristics and the use of the Gabor wavelet
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