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Semi-automatic measurements of foot morphological parameters from 3D plantar foot scans

BACKGROUND: Foot healthcare research is focusing increasingly on personalized orthotic and prosthetic devices to address patient-specific morphology and ailments. Customization requires advanced 3D image processing tools to assess foot and leg geometrical parameters and alterations. The aim of this...

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Autores principales: Rogati, Giulia, Leardini, Alberto, Ortolani, Maurizio, Caravaggi, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7972185/
https://www.ncbi.nlm.nih.gov/pubmed/33731179
http://dx.doi.org/10.1186/s13047-021-00461-z
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author Rogati, Giulia
Leardini, Alberto
Ortolani, Maurizio
Caravaggi, Paolo
author_facet Rogati, Giulia
Leardini, Alberto
Ortolani, Maurizio
Caravaggi, Paolo
author_sort Rogati, Giulia
collection PubMed
description BACKGROUND: Foot healthcare research is focusing increasingly on personalized orthotic and prosthetic devices to address patient-specific morphology and ailments. Customization requires advanced 3D image processing tools to assess foot and leg geometrical parameters and alterations. The aim of this study is to present a new software for the measurement of the foot shape from 3D scans of the foot plantar surface. METHODS: A Kinect-based scanning device was used to acquire the 3D foot shape of 44 healthy subjects. A software was developed in Matlab to measure the foot main morphological parameters from foot scans. Principal Component Analysis was used to orientate the foot scans with respect to the same reference system. Accuracy, via percentage errors and Bland-Altman plots, and correlation of the software-based foot parameters were assessed against manual measurements. A normalized Arch Volume Index (nAVI) was proposed and correlated to the traditional Arch Index. Test-retest Intraclass Correlation Coefficient was used to assess the inter-session repeatability of foot measurements. RESULTS: The average percentage error between software and manual measurements was 1.2 ± 0.8% for foot length, 9.1 ± 3.7% for foot width, 22.3 ± 13.5% for arch height and 23.1 ± 12.7% for arch depth. Very strong correlations were observed for foot length (R = 0.97) and foot width (R = 0.83), and strong correlations for arch height (R = 0.62) and arch depth (R = 0.74). nAVI was negatively correlated to the Arch Index (R = -0.54). A small difference was found between software and manual measurements of foot length (Δ = 0.92 mm), a software overestimation of foot width (Δ = 8.6 mm) and underestimation of arch height (Δ = -1.4%) and arch depth (Δ = -11%). Moderate to excellent repeatability was observed for all measurements (0.67–0.99). CONCLUSIONS: The present software appears capable to estimate the foot main morphological parameters without the need for skin markers or for identification of anatomical landmarks. Moreover, measurements are not affected by the foot orientation on the scanning device. The good accuracy and repeatability of measurements make the software a potentially useful operator-independent tool for the assessment of foot morphological alterations and for orthotics customization. nAVI may be used for a more realistic classification of foot types when 3D foot images are available.
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spelling pubmed-79721852021-03-19 Semi-automatic measurements of foot morphological parameters from 3D plantar foot scans Rogati, Giulia Leardini, Alberto Ortolani, Maurizio Caravaggi, Paolo J Foot Ankle Res Research BACKGROUND: Foot healthcare research is focusing increasingly on personalized orthotic and prosthetic devices to address patient-specific morphology and ailments. Customization requires advanced 3D image processing tools to assess foot and leg geometrical parameters and alterations. The aim of this study is to present a new software for the measurement of the foot shape from 3D scans of the foot plantar surface. METHODS: A Kinect-based scanning device was used to acquire the 3D foot shape of 44 healthy subjects. A software was developed in Matlab to measure the foot main morphological parameters from foot scans. Principal Component Analysis was used to orientate the foot scans with respect to the same reference system. Accuracy, via percentage errors and Bland-Altman plots, and correlation of the software-based foot parameters were assessed against manual measurements. A normalized Arch Volume Index (nAVI) was proposed and correlated to the traditional Arch Index. Test-retest Intraclass Correlation Coefficient was used to assess the inter-session repeatability of foot measurements. RESULTS: The average percentage error between software and manual measurements was 1.2 ± 0.8% for foot length, 9.1 ± 3.7% for foot width, 22.3 ± 13.5% for arch height and 23.1 ± 12.7% for arch depth. Very strong correlations were observed for foot length (R = 0.97) and foot width (R = 0.83), and strong correlations for arch height (R = 0.62) and arch depth (R = 0.74). nAVI was negatively correlated to the Arch Index (R = -0.54). A small difference was found between software and manual measurements of foot length (Δ = 0.92 mm), a software overestimation of foot width (Δ = 8.6 mm) and underestimation of arch height (Δ = -1.4%) and arch depth (Δ = -11%). Moderate to excellent repeatability was observed for all measurements (0.67–0.99). CONCLUSIONS: The present software appears capable to estimate the foot main morphological parameters without the need for skin markers or for identification of anatomical landmarks. Moreover, measurements are not affected by the foot orientation on the scanning device. The good accuracy and repeatability of measurements make the software a potentially useful operator-independent tool for the assessment of foot morphological alterations and for orthotics customization. nAVI may be used for a more realistic classification of foot types when 3D foot images are available. BioMed Central 2021-03-17 /pmc/articles/PMC7972185/ /pubmed/33731179 http://dx.doi.org/10.1186/s13047-021-00461-z Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Rogati, Giulia
Leardini, Alberto
Ortolani, Maurizio
Caravaggi, Paolo
Semi-automatic measurements of foot morphological parameters from 3D plantar foot scans
title Semi-automatic measurements of foot morphological parameters from 3D plantar foot scans
title_full Semi-automatic measurements of foot morphological parameters from 3D plantar foot scans
title_fullStr Semi-automatic measurements of foot morphological parameters from 3D plantar foot scans
title_full_unstemmed Semi-automatic measurements of foot morphological parameters from 3D plantar foot scans
title_short Semi-automatic measurements of foot morphological parameters from 3D plantar foot scans
title_sort semi-automatic measurements of foot morphological parameters from 3d plantar foot scans
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7972185/
https://www.ncbi.nlm.nih.gov/pubmed/33731179
http://dx.doi.org/10.1186/s13047-021-00461-z
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