MATEC Web Conf.
Volume 135, 20178th International Conference on Mechanical and Manufacturing Engineering 2017 (ICME’17)
|Number of page(s)||11|
|Published online||20 November 2017|
Correlation of Loaded and Unloaded Foot Area With Arch Index in Younger Flatfoot
Mechanical Engineering Dept., Diponegoro University, Semarang, Indonesia
2 Faculty of Public Health, HAKLI Institute of Health Science Semarang, Indonesia
* Corresponding author: firstname.lastname@example.org
Harris & Beath claimed 23% of human kind population is indicated flatfoot. Identifying flatfoot is by using wet foot test. This footprint is not accurate because of the difficulty to make sure the patient stand upright. Another way is using x-ray to determine height of arch which is a distance from medial longitudinal foot arch to the ground. If the distance is less than certain level, so the foot type is included as flatfoot. Other method proposed by Kulkarni et al. using the footprint index (FPI) which is the ratio of B intercept to A intercept, where the footprint was obtained from pedobarography image. If FPI is lower than 0.63, it is categorized as flatfoot. Another method to determine arch type which is widely used is Cavanagh’s Arch Index (AI) from division of mid foot area to entire footprint area (excluding the toes). If AI>0.26, then the foot type is flatfoot. This study is to learn the correlation between entire loaded and unloaded foot area with Cavanag’s AI. The entire loaded foot and footprint area for evaluating AI derived from a digital footprint modified from document scanner, while the entire unloaded foot area derived from a 3D scanner for foot orthotic. One hundred and two healthy asked voluntarily for doing footprint. From 102 subjects found 63 participants identified as flatfoot, 31 subjects are normal feet and 8 subjects identified as high arch. A series of 3 x 3 repeated measures ANOVAs were used to determine statistical differences (α<0.05). A significant interaction existed between ratio of entire loaded and unloaded foot area (RFA) subject to all categories of AI (p<0.05) also a correlation coefficient of r=0.67 has found between RFA and AI on foot type of flatfoot which means that flatfoot can be indicated by RFA.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.