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

Gait analysis Gait events Locomotion Pressure insoles Wearable sensors

Journal

Journal of biomechanics
ISSN: 1873-2380
Titre abrégé: J Biomech
Pays: United States
ID NLM: 0157375

Informations de publication

Date de publication:
11 10 2021
Historique:
received: 08 04 2021
revised: 21 07 2021
accepted: 09 08 2021
pubmed: 30 8 2021
medline: 26 10 2021
entrez: 29 8 2021
Statut: ppublish

Résumé

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-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 = 310 mm

Identifiants

pubmed: 34455233
pii: S0021-9290(21)00456-5
doi: 10.1016/j.jbiomech.2021.110687
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

110687

Subventions

Organisme : Department of Health
Pays : United Kingdom

Informations de copyright

Copyright © 2021 Elsevier Ltd. All rights reserved.

Auteurs

F Salis (F)

Department of Biomedical Sciences, University of Sassari, Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Sassari, Italy. Electronic address: fsalis1@uniss.it.

S Bertuletti (S)

Department of Biomedical Sciences, University of Sassari, Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Sassari, Italy. Electronic address: sbertuletti@uniss.it.

T Bonci (T)

Insigneo Institute and Department of Mechanical Engineering, University of Sheffield, Sheffield, UK. Electronic address: t.bonci@sheffield.ac.uk.

U Della Croce (U)

Department of Biomedical Sciences, University of Sassari, Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Sassari, Italy. Electronic address: dellacro@uniss.it.

C Mazzà (C)

Insigneo Institute and Department of Mechanical Engineering, University of Sheffield, Sheffield, UK. Electronic address: c.mazza@sheffield.ac.uk.

A Cereatti (A)

Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Sassari, Italy; Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy. Electronic address: andrea.cereatti@polito.it.

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Classifications MeSH