Preventive strategy of flatfoot deformity using fully automated procedure

Abstract

A non-invasive, no radiation, out-of-hospital automated system is proposed to identify low arch integrated in the design and manufacturing of personalized orthoses using parametric modelling. The aim of the design process is to integrate assistive technology with assessment and prevent low arch progressing to a more serious case - flatfoot. In the automated procedure, we developed an assessment method including reliable thresholds of foot type classification and test protocol to reduce interferences due to preceding activities, an automation to translate scanned data into parametric design for orthotic customization, finite element model evaluating effectiveness of the personalized design, and a personalized comparative test to evaluate the long-term improvement of foot arch shape. Our low arch threshold established by subject-specific 3D models reduced the misclassification rate from 55%, as previously reported to 6.9%. Individuals who engaged in sedentary activity (i.e. sitting) had the greater change in arch height compared to active activity (i.e. standing and walking), which is more likely to affect the obtained measure. Therefore, a test protocol now states that participants are not allowed to sit over 100 min prior the measurement to reduce such interference. We have proposed and tested an automated algorithm to translate scanned data including seven foot's parameters into customised parametric design of the insert. The method decreases the required time of orthotic computer-aided design from over 3 h to less than 2 min. A finite element analysis procedure was additionally developed to assess the performance of geometries and material of designed orthotic based on the distribution of plantar pressure and internal stress. The personalized comparative assessment based on midfoot contact area was carried out periodically for follow-up and the orthotic could be re-designed if necessary. The proposed automated procedure develops a pre-screening system to distinguish low arch and provide preventatives before it becomes symptomatic. Furthermore, non-symptom flatfoot can be detected at early stages and referred to medics for further diagnosis or treatment.

Keywords: 3D foot scans; Abbreviations: Navicular height (NH); Confidence interval (CI); Finite element (FE); Finite element analysis (FEA), Computer-aided design (CAD); Foot orthoses; Low arch; Normalized Navicular Height Truncated; Normalized navicular height (NNH); Normalized navicular height truncated (NNHt); Parametric modelling, Finite element analysis; Standard deviation (SD); Standard error (SE).