Study on foot-type classification for young adults based on static and dynamic plantar pressure distribution. (May 2022)

• Record Type: Journal Article
• Authors: Tang, Xinyao; Wang, Xupeng; Ji, Xiaomin; Wang, Yunqian; Chen, Wenhui; Wei, Yuchen; Zhou, Yawen
• Is Part Of: Advances in mechanical engineering. Volume 14:Number 5(2022)
• Publication Date: 2022-05
• Subjects: Foot type -- plantar pressure distribution -- arch index -- isobaric region -- bitmap index; Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1177/16878132221097904
• Languages: English
• ISSNs: 1687-8132

Abstract

The application of an effective and reliable foot type classification method is very important for foot type judgment, injury risk assessment, and correction. Therefore, this paper mainly aims to propose a new foot type classification method for young people based on bitmap index (BI), compare it with the traditional footprint classification method, and put forward and analyze the factors affecting foot type classification. Thirty-one healthy volunteers were asked to perform two types tests in order to study the plantar pressure distribution with static and dynamic conditions, the first type is footprint test with full load of static, and the other type is plantar pressure distribution, which contains four different tests: no load, half load, and full load of static state, as well as dynamic plantar pressure distribution during process of walking. The Intraclass Correlation Coefficient results (ICC) were good reliable and reproducible for BI value with dynamic test (DT-BI value 0.738, 95% confidence interval [0.535, 0.848], α = 0 . 768 ) and full-load (FL-BI value 0.725 [0.281, 0.814], α = 0 . 725, p < 0.001), obtained with individual measures and a two-way mixed-effects model. It can be seen from Kappa coefficient and density map that DT-BI has high classification accuracy. Classification of foot type based on bitmap index values showed good reliability in people with varying BMI, which can help clinicians and researchers segment the sample population to better distinguish between different foot types of activity, gait or treatment effects.