Yamashita T, Yamashita K, Sato M, Kawasumi M, Ata S. Analysis of skeletal characteristics of flat feet using three-dimensional foot scanner and digital footprint.
Biomed Eng Online 2022;
21:56. [PMID:
35945533 PMCID:
PMC9361570 DOI:
10.1186/s12938-022-01021-7]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 07/20/2022] [Indexed: 11/25/2022] Open
Abstract
Background
Flat feet increase the risk of knee osteoarthritis and contribute to frailty, which may lead to worse life prognoses. The influence of the foot skeletal structure on flat feet is not yet entirely understood. Footprints are often used to evaluate feet. However, footprint-based measurements do not reflect the underlying structures of feet and are easily confounded by soft tissue. Three-dimensional evaluation of the foot shape can reveal the characteristics of flat feet. Therefore, foot shape evaluations have garnered increasing research interest. This study aimed to determine the correlation between the three-dimensional (3D) features of the foot and the measurement results of footprint and to predict the evaluation results of flat feet from the footprint based on the 3D features. Finally, the three-dimensional characteristics of flat feet, which cannot be revealed by footprint, were determined.
Methods
A total of 403 individuals (40–89 years) participated in this study. The proposed system was developed to identify seven skeletal features that were expected to be associated with flat feet. The loads on the soles of the feet were measured in a static standing position and with a digital footprint device. Specifically, two footprint indices were calculated: the Chippaux–Smirak index (CSI) and the Staheli index (SI). In the analysis, comparisons between male and female measurement variables were performed using the Student’s t test. The relationships between the 3D foot features and footprint index parameters were determined by employing the Pearson correlation coefficient. Multiple linear regression was utilized to identify 3D foot features that were strongly associated with the CSI and SI. Foot features identified as significant in the multivariate regression analysis were compared based on a one-way analysis of variance (ANOVA) with Tukey’s post hoc test.
Results
The CSI and SI were highly correlated with the instep height (IH) and navicular height (NH) of the 3D foot scanning system and were also derived from multiple regression analysis. In addition to the NH and IH, the indicators of the forefoot, transverse arch width, and transverse arch height were considered. In the flat foot group with CSI values above 62.7%, NH was 13.5% (p < 0.001) for males and 14.9% (p = 0.01) for females, and the axis of the bone distance was 5.3% (p = 0.05) for males and 4.9% (p = 0.10) for females. In particular, for CSI values above 62.7% and NH values below 13%, the axis of the bone distance was large and the foot skeleton was deformed.
Conclusions
Decreased navicular bone height could be evaluated with the 3D foot scanning system even when flat feet were not detected from the footprint. The results indicate that the use of quantitative indices for 3D foot measurements is important when evaluating the flattening of the foot.
Trial registration number UMIN000037694.
Name of the registry: University Hospital Medical Information Network Registry.
Date of registration: August 15, 2019.
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