Smart Insoles-based Gait Symmetry Detection for People with Lower-limb Amputation

Luigi D'Arco, Haiying Wang, Carolyn Wilson, Ezio Preatoni, Elena Seminati, Grant Trewartha, Jill Cundell, Huiru Zheng

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Abstract

Lower limb prostheses offer mobility restoration to individuals who underwent amputation, yet they often introduce movement alterations that can affect physical health over time. While monitoring and understanding these alterations are crucial for designing tailored rehabilitation plans, existing technologies are primarily confined to clinical settings and lack representation of real-world mobility scenarios. This study investigates the use of smart insoles as a cost-effective means to assess walking symmetry and effectiveness in individuals with prostheses. Ten participants, including six lower-limb prosthesis users and four healthy subjects, were recruited to compare gait parameters and symmetry during a 2-minute walking test. The proposed methodology involves employing a Finite State Machine (FSM) to extract gait phases and subsequent kinematic and kinetic parameters. States of the FSM correspond to gait subphases, while transitions are managed by a fuzzy c-means clustering model. The solution demonstrated robust step count recognition, with an error rate of 1.24%. Additionally, when benchmarked against the GAITRite mat, a commonly used device for gait analysis, a mean absolute error of 0.05 seconds was identified in terms of stride time. Comparison between prosthetic and healthy subjects revealed distinct patterns. Specifically, primary differences have been identified in the symmetry of stance and swing times, where healthy subjects exhibited a higher symmetry percentage, with values of 93.75% and 92.95% respectively, against percentages of 88.82% and 83.05% for prosthetic sub- jects. These findings underscore the potential of smart insoles for ubiquitous monitoring of walking dynamics in daily life. By facilitating the early detection of asymmetries and anomalies, this study lays the foundations for the development of future solutions aimed at improving the quality of life of lower limb prosthesis users by sharing these insights with healthcare professionals who can define tailored rehabilitation strategies.
Original languageEnglish
Title of host publicationProceedings of the 35th Irish Systems and Signals Conference, ISSC 2024
EditorsHuiru Zheng, Ian Cleland, Adrian Moore, Haiying Wang, David Glass, Joe Rafferty, Raymond Bond, Jonathan Wallace
Number of pages7
ISBN (Electronic)979-8-3503-5298-6
DOIs
Publication statusPublished online - 29 Jul 2024
Event35th Irish Systems and Signals Conference -
Duration: 13 Jun 202414 Jun 2024
https://www.ulster.ac.uk/events/research/35th-irish-signals-and-systems-conference-issc-2024

Publication series

NameProceedings of the 35th Irish Systems and Signals Conference, ISSC 2024

Conference

Conference35th Irish Systems and Signals Conference
Period13/06/2414/06/24
Internet address

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • Gait Analysis
  • Smart Insoles
  • Amputees
  • Gait Symmetry
  • Finite State Machine
  • Amputee

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