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Automated Spatial Pattern Analysis for Identification of Foot Arch Height From 2D Foot Prints.

Julien Lucas1, Kinda Khalaf2, James Charles3,4

  • 1Department of Biology and Computer Science, University of Poitiers, Poitiers, France.

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Summary

Automated analysis of digitized footprints using Gabor wavelets can accurately classify foot arch type. This method, combining mean bending energy and foot perimeter, offers a time-effective tool for clinical diagnostics.

Keywords:
bending energycomplexityfoot arch heightnon-linear dynamicswavelet analysis

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Area of Science:

  • Biomechanics
  • Medical Imaging
  • Computational Anatomy

Background:

  • Foot arch height is crucial for predicting foot pathology, particularly in aging individuals.
  • Current footprint analysis methods are time-consuming due to manual processing requirements.

Purpose of the Study:

  • To investigate an automated method for determining foot type using Gabor wavelet features from digitized footprints.
  • To enable timely assessment of foot type and facilitate focused interventions.

Main Methods:

  • Collected 280 digitized footprints for analysis.
  • Utilized in-house MATLAB codes to extract features like area, perimeter, curvature, circularity, 2nd wavelet moment, mean bending energy (MBE), and entropy.
  • Compared results to a gold standard using Spearman's Correlation and multiple linear regression, with significance at p < 0.05.

Main Results:

  • The combination of MBE and foot perimeter provided the best classification results (ANOVA, p < 0.0001).
  • Achieved a clinical reliability of up to 87% using newly established cutoff values.
  • Automated wavelet-based classification demonstrated comparability to state-of-the-art methods.

Conclusions:

  • Automated wavelet-based foot type classification from 2D plantar images is a viable alternative to current methods.
  • This approach offers a cost-effective and time-efficient tool for clinical diagnostics.
  • Accurate foot type classification can aid in early detection and management of foot pathologies.