Heel pad's hyperelastic properties and gait parameters reciprocal modelling by a Gaussian Mixture Model and Extreme Gradient Boosting framework

Luca Quagliato, Sewon Kim, Olamide Robiat Hassan, Taeyong Lee

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Gait analysis and heel pad mechanical properties have been largely studied by physicians and biomechanical engineers alike. However, only a few contributions deal with the intertwining relationship between these two essential aspects and no research seems to propose a modeling approach to quantitatively correlate them. To bridge this gap, indentation experiments on the heel pad and gait analysis through motion capture camera were carried out on a group composed of 40 male and female subjects in the 20′s to 50′s. To establish a robust correlation between these two sets of parameters, the Gaussian Mixture Model (GMM) features’ enhancement technique was employed and combined with the Extreme Gradient Boosting (XGB) regressor. The hyperelastic constants from models, together with the gait parameters, were employed as both features and target variables in the GMM-XGB architecture showing the ambivalence of the solution and deviations between 5% and 8% in most cases. The results show the strong reciprocal correlation between the individual's foot plantar soft tissue's mechanical response and the gait parameters and pave the way for further investigations in the field of biomechanics.

Original languageEnglish
Article number107818
JournalBiomedical Signal Processing and Control
Volume107
DOIs
StatePublished - Sep 2025

Bibliographical note

Publisher Copyright:
© 2025 Elsevier Ltd

Keywords

  • Extreme Gradient Boosting (XGB)
  • Gait analysis
  • Gaussian Mixture Model (GMM)
  • Heel pad mechanical properties
  • Indentation

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