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

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Article asserts that the foot is a vital organ, as it stabilizes the impact forces between the human skeletal system and the ground. The authors present an instep girth measurement algorithm, and they used a pixel per metric algorithm for measurement; these algorithms were accordingly integrated with the application.

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17 p.

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Rafiq, Riyad Bin; Hoque, Kazi Miftahul; Kabir, Muhammad Ashad; Ahmed, Sayed & Laird, Craig December 6, 2022.

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This article is part of the collection entitled: UNT Scholarly Works and was provided by the UNT College of Engineering to the UNT Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 12 times, with 4 in the last month. More information about this article can be viewed below.

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Article asserts that the foot is a vital organ, as it stabilizes the impact forces between the human skeletal system and the ground. The authors present an instep girth measurement algorithm, and they used a pixel per metric algorithm for measurement; these algorithms were accordingly integrated with the application.

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17 p.

Notes

Abstract: 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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  • Sensors, 22(23), MDPI, December 6, 2022, pp. 1-17

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  • Publication Title: Sensors
  • Volume: 22
  • Issue: 23
  • Peer Reviewed: Yes

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  • December 6, 2022

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  • Oct. 12, 2023, 2:19 p.m.

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  • Nov. 2, 2023, 1:56 p.m.

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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, article, December 6, 2022; (https://digital.library.unt.edu/ark:/67531/metadc2179469/: accessed February 26, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Engineering.

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