Journal article Open Access

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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    <subfield code="u">Department of Biomedical Sciences, University of Sassari, Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Sassari, Italy;</subfield>
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    <subfield code="u">Department of Biomedical Sciences, University of Sassari, Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Sassari, Italy</subfield>
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    <subfield code="u">Department of Biomedical Sciences, University of Sassari, Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Sassari, Italy;</subfield>
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    <subfield code="a">A method for gait events detection based on low spatial resolution pressure insoles data</subfield>
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    <subfield code="a">&lt;p&gt;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&amp;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&amp;nbsp;=&amp;nbsp;310&amp;nbsp;mm&lt;sup&gt;2&lt;/sup&gt;), sampling at 100&amp;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&amp;nbsp;ms and 10&amp;nbsp;ms, respectively). Similarly, the errors in estimating stance duration and step duration averaged 20&amp;nbsp;ms and &amp;lt;10&amp;nbsp;ms, respectively. By selecting appropriate thresholds, the method may be easily applied to other pressure insoles featuring similar requirements.&lt;/p&gt;

&lt;p&gt;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&amp;#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&amp;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.&lt;/p&gt;</subfield>
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