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The Multifeature Gait Score: An accurate way to assess gait quality

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  • Khaireddine Ben Mansour
  • Philippe Gorce
  • Nasser Rezzoug

Abstract

Purpose: This study introduces a novel way to accurately assess gait quality. This new method called Multifeature Gait Score (MGS) is based on the computation of multiple parameters characterizing six aspects of gait (temporal, amplitude, variability, regularity, symmetry and complexity) quantified with one inertial sensor. According to the aspects described, parameters were aggregated into partial scores to indicate the altered aspect in the case of abnormal patterns. In order to evaluate the overall gait quality, partial scores were averaged to a global score. Methods: The MGS was computed for 3 groups namely: healthy adult (10 subjects), sedentary elderly (11 subjects) and active elderly (20 subjects). Data were gathered from an inertial sensor located at the lumbar region during two sessions of 12m walking. Results: The results based on ANOVA and Tukey tests showed that the partial scores with the exception of those which describe the symmetry aspect were able to discriminate between groups (p

Suggested Citation

  • Khaireddine Ben Mansour & Philippe Gorce & Nasser Rezzoug, 2017. "The Multifeature Gait Score: An accurate way to assess gait quality," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-12, October.
    • Handle: RePEc:plo:pone00:0185741
    DOI: 10.1371/journal.pone.0185741
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    References listed on IDEAS

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    1. I. T. Jolliffe, 1972. "Discarding Variables in a Principal Component Analysis. I: Artificial Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 21(2), pages 160-173, June.
    2. K. Ben Mansour & N. Rezzoug & P. Gorce, 2015. "Comparison between several locations of gyroscope for gait events detection," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 18(S1), pages 1996-1997, October.
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    1. Tania Aznielle-Rodríguez & Lídice Galán-García & Marlis Ontivero-Ortega & Karen Aguilar-Mateu & Ana M Castro-Laguardia & Ana Fernández-Nin & Daysi García-Agustín & Mitchell Valdés-Sosa, 2023. "Relationship between gait parameters and cognitive indexes in adult aging," PLOS ONE, Public Library of Science, vol. 18(9), pages 1-15, September.

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