TY - JOUR
T1 - OptiFit
T2 - Computer-Vision-Based Smartphone Application to Measure the Foot from Images and 3D Scans
AU - Rafiq, Riyad Bin
AU - Hoque, Kazi Miftahul
AU - Kabir, Ashad
AU - Ahmed, Sayed
AU - Laird, Craig
N1 - Funding Information:
The APC was funded by Foot Balance Technology Pty. Ltd.
Publisher Copyright:
© 2022 by the authors.
PY - 2022/12/6
Y1 - 2022/12/6
N2 - 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.
AB - 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.
KW - foot measurement
KW - computer vision
KW - image processing
KW - 3D scan
KW - algorithm
KW - smartphone app
KW - custom footwear
KW - Computers
KW - Humans
KW - Male
KW - Shoes
KW - Foot/diagnostic imaging
KW - Algorithms
KW - Female
KW - Smartphone
UR - http://www.scopus.com/inward/record.url?scp=85143825013&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85143825013&partnerID=8YFLogxK
U2 - 10.3390/s22239554
DO - 10.3390/s22239554
M3 - Article
C2 - 36502254
VL - 22
JO - Sensors (Switzerland)
JF - Sensors (Switzerland)
SN - 1424-8220
IS - 23
M1 - 9554
ER -