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A method for gait events detection based on low spatial resolution pressure insoles data

Salis, Francesca; Bertuletti, Stefano; Bonci, Tecla; Croce, Ugo Della; Mazzà, Claudia; Cereatti, Andrea


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{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>Abstract: The accurate identification of initial and final foot contacts is a crucial prerequisite for obtaining a reliable estimation of spatio-temporal parameters of gait. Well-accepted gold standard techniques in this field are force platforms and instrumented walkways, which provide a direct measure of the foot&ndash;ground reaction forces. Nonetheless, these tools are expensive, non-portable and restrict the analysis to laboratory settings. Instrumented insoles with a reduced number of pressure sensing elements might overcome these limitations, but a suitable method for gait events identification has not been adopted yet. The aim of this paper was to present and validate a method aiming at filling such void, as applied to a system including two insoles with 16 pressure sensing elements (element area&nbsp;=&nbsp;310&nbsp;mm<sup>2</sup>), sampling at 100&nbsp;Hz. Gait events were identified exploiting the sensor redundancy and a cluster-based strategy. The method was tested in the laboratory against force platforms on nine healthy subjects for a total of 801 initial and final contacts. Initial and final contacts were detected with low average errors of (about 20&nbsp;ms and 10&nbsp;ms, respectively). Similarly, the errors in estimating stance duration and step duration averaged 20&nbsp;ms and &lt;10&nbsp;ms, respectively. By selecting appropriate thresholds, the method may be easily applied to other pressure insoles featuring similar requirements.</p>\n\n<p>This work was supported by the Mobilise-D project that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 820820. This Joint Undertaking receives support from the European Union&#39;s Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA). Content in this publication reflects the authors&rsquo; view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Department of Biomedical Sciences, University of Sassari, Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Sassari, Italy;", 
      "@type": "Person", 
      "name": "Salis, Francesca"
    }, 
    {
      "affiliation": "Department of Biomedical Sciences, University of Sassari, Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Sassari, Italy;", 
      "@type": "Person", 
      "name": "Bertuletti, Stefano"
    }, 
    {
      "affiliation": "Insigneo Institute for in silico Medicine and Department of Mechanical Engineering, University of Sheffield, Sheffield, UK", 
      "@type": "Person", 
      "name": "Bonci, Tecla"
    }, 
    {
      "affiliation": "Department of Biomedical Sciences, University of Sassari, Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Sassari, Italy", 
      "@type": "Person", 
      "name": "Croce, Ugo Della"
    }, 
    {
      "affiliation": "Insigneo Institute for in silico Medicine and Department of Mechanical Engineering, University of Sheffield, Sheffield, UK", 
      "@type": "Person", 
      "name": "Mazz\u00e0, Claudia"
    }, 
    {
      "affiliation": "Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy", 
      "@type": "Person", 
      "name": "Cereatti, Andrea"
    }
  ], 
  "headline": "A method for gait events detection based on low spatial resolution pressure insoles data", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2021-08-13", 
  "url": "https://zenodo.org/record/5526474", 
  "keywords": [
    "gait analysis", 
    "wearable sensors", 
    "pressure insoles", 
    "locomotion", 
    "gait events"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.5526474", 
  "@id": "https://doi.org/10.5281/zenodo.5526474", 
  "@type": "ScholarlyArticle", 
  "name": "A method for gait events detection based on low spatial resolution pressure insoles data"
}
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