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OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans

The foot is a vital organ, as it stabilizes the impact forces between the human skeletal system and the ground. Hence, precise foot dimensions are essential not only for custom footwear design, but also for the clinical treatment of foot health. Most existing research on measuring foot dimensions de...

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Autores principales: Rafiq, Riyad Bin, Hoque, Kazi Miftahul, Kabir, Muhammad Ashad, Ahmed, Sayed, Laird, Craig
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9739363/
https://www.ncbi.nlm.nih.gov/pubmed/36502254
http://dx.doi.org/10.3390/s22239554
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author Rafiq, Riyad Bin
Hoque, Kazi Miftahul
Kabir, Muhammad Ashad
Ahmed, Sayed
Laird, Craig
author_facet Rafiq, Riyad Bin
Hoque, Kazi Miftahul
Kabir, Muhammad Ashad
Ahmed, Sayed
Laird, Craig
author_sort Rafiq, Riyad Bin
collection PubMed
description The foot is a vital organ, as it stabilizes the impact forces between the human skeletal system and the ground. Hence, precise foot dimensions are essential not only for custom footwear design, but also for the clinical treatment of foot health. Most existing research on measuring foot dimensions depends on a heavy setup environment, which is costly and ineffective for daily use. In addition, there are several smartphone applications online, but they are not suitable for measuring the exact foot shape for custom footwear, both in clinical practice and public use. In this study, we designed and implemented computer-vision-based smartphone application OptiFit that provides the functionality to automatically measure the four essential dimensions (length, width, arch height, and instep girth) of a human foot from images and 3D scans. We present an instep girth measurement algorithm, and we used a pixel per metric algorithm for measurement; these algorithms were accordingly integrated with the application. Afterwards, we evaluated our application using 19 medical-grade silicon foot models (12 males and 7 females) from different age groups. Our experimental evaluation shows that OptiFit could measure the length, width, arch height, and instep girth with an accuracy of 95.23%, 96.54%, 89.14%, and 99.52%, respectively. A two-tailed paired t-test was conducted, and only the instep girth dimension showed a significant discrepancy between the manual measurement (MM) and the application-based measurement (AM). We developed a linear regression model to adjust the error. Further, we performed comparative analysis demonstrating that there were no significant errors between MM and AM, and the application offers satisfactory performance as a foot-measuring application. Unlike other applications, the iOS application we developed, OptiFit, fulfils the requirements to automatically measure the exact foot dimensions for individually fitted footwear. Therefore, the application can facilitate proper foot measurement and enhance awareness to prevent foot-related problems caused by inappropriate footwear.
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spelling pubmed-97393632022-12-11 OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans Rafiq, Riyad Bin Hoque, Kazi Miftahul Kabir, Muhammad Ashad Ahmed, Sayed Laird, Craig Sensors (Basel) Article The foot is a vital organ, as it stabilizes the impact forces between the human skeletal system and the ground. Hence, precise foot dimensions are essential not only for custom footwear design, but also for the clinical treatment of foot health. Most existing research on measuring foot dimensions depends on a heavy setup environment, which is costly and ineffective for daily use. In addition, there are several smartphone applications online, but they are not suitable for measuring the exact foot shape for custom footwear, both in clinical practice and public use. In this study, we designed and implemented computer-vision-based smartphone application OptiFit that provides the functionality to automatically measure the four essential dimensions (length, width, arch height, and instep girth) of a human foot from images and 3D scans. We present an instep girth measurement algorithm, and we used a pixel per metric algorithm for measurement; these algorithms were accordingly integrated with the application. Afterwards, we evaluated our application using 19 medical-grade silicon foot models (12 males and 7 females) from different age groups. Our experimental evaluation shows that OptiFit could measure the length, width, arch height, and instep girth with an accuracy of 95.23%, 96.54%, 89.14%, and 99.52%, respectively. A two-tailed paired t-test was conducted, and only the instep girth dimension showed a significant discrepancy between the manual measurement (MM) and the application-based measurement (AM). We developed a linear regression model to adjust the error. Further, we performed comparative analysis demonstrating that there were no significant errors between MM and AM, and the application offers satisfactory performance as a foot-measuring application. Unlike other applications, the iOS application we developed, OptiFit, fulfils the requirements to automatically measure the exact foot dimensions for individually fitted footwear. Therefore, the application can facilitate proper foot measurement and enhance awareness to prevent foot-related problems caused by inappropriate footwear. MDPI 2022-12-06 /pmc/articles/PMC9739363/ /pubmed/36502254 http://dx.doi.org/10.3390/s22239554 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rafiq, Riyad Bin
Hoque, Kazi Miftahul
Kabir, Muhammad Ashad
Ahmed, Sayed
Laird, Craig
OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans
title OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans
title_full OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans
title_fullStr OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans
title_full_unstemmed OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans
title_short OptiFit: Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans
title_sort optifit: computer-vision-based smartphone application to measure the foot from images and 3d scans
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9739363/
https://www.ncbi.nlm.nih.gov/pubmed/36502254
http://dx.doi.org/10.3390/s22239554
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