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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-9739363 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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