Impact of anthropometric characteristics on the medial longitudinal arch in static and dynamic loading using photogrammetry images

Al-Kharaz, Ali A. and Chong, Albert K. (2020) Impact of anthropometric characteristics on the medial longitudinal arch in static and dynamic loading using photogrammetry images. Series on Biomechanics, 34 (2). pp. 56-61. ISSN 1313-2458


Abstract

The Medial Longitudinal Arch (MLA) of the foot plays an important role in daily activities. Therefore, evaluation of the MLA during loading is essential. The aim of this study was to test a new three-dimensional method using close-range photogrammetry to measure the MLA while sitting for static partial loading and during the stance phase of walking for dynamic loading and to determine the impact of age, height, weight, BMI and foot length on the MLA. Thirty-three healthy adults (18 males and 15 females) were tested. The self-calibration bundle adjustment was used to measure five reference points on the right foot. The results demonstrated that there was a significant correlation between age and dynamic loading in the four stance phases. The relationship between the MLA and BMI was positive and statistically significant. While sitting, the MLA tended to be high. The reliability of test-retest in dynamic loading was very accurate (0.86). These results validated the importance of the longitudinal arch angle for the foot during physical activity and physical therapy, and may add information in the clinical arena.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 -)
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 -)
Date Deposited: 23 Jul 2020 04:57
Last Modified: 31 Aug 2020 05:27
Uncontrolled Keywords: close-range photogrammetry, medial longitudinal arch, sitting, gait
Fields of Research (2008): 09 Engineering > 0903 Biomedical Engineering > 090302 Biomechanical Engineering
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
URI: http://eprints.usq.edu.au/id/eprint/38877

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