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Classifying sitting, standing, and walking using plantar force data

Abstract

Prolonged static weight-bearing at work may increase the risk of developing plantar fasciitis (PF). However, to establish a causal relationship between weight-bearing and PF, a low-cost objective measure of workplace behaviors is needed. This proof-of-concept study assesses the classification accuracy and sensitivity of low-resolution plantar pressure measurements in distinguishing workplace postures. Plantar pressure was measured using an in-shoe measurement system in eight healthy participants while sitting, standing, and walking. Data was resampled to simulate on/off characteristics of 24 plantar force sensitive resistors. The top 10 sensors were evaluated using leave-one-out cross-validation with machine learning algorithms: support vector machines (SVMs), decision tree (DT), discriminant analysis (DA), and k-nearest neighbors (KNN). SVM and DT best classified sitting, standing, and walking. High classification accuracy was obtained with five sensors (98.6% and 99.1% accuracy, respectively) and even a single sensor (98.4% and 98.4%, respectively). The central forefoot and the medial and lateral midfoot were the most important classification sensor locations. On/off plantar pressure measurements in the midfoot and central forefoot can accurately classify workplace postures. These results provide the foundation for a low-cost objective tool to classify and quantify sedentary workplace postures.

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Funding

This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) EGP 491213-15 and the Simon Fraser University Community Trust Endowment Fund.

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Correspondence to Kohle J. Merry.

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Michael Ryan is a salaried employee of Kintec Footlabs Inc.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Merry, K.J., Macdonald, E., MacPherson, M. et al. Classifying sitting, standing, and walking using plantar force data. Med Biol Eng Comput 59, 257–270 (2021). https://doi.org/10.1007/s11517-020-02297-4

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  • DOI: https://doi.org/10.1007/s11517-020-02297-4

Keywords

  • Pedobarography
  • Pattern recognition
  • Posture differentiation
  • Plantar fasciitis
  • Weight-bearing