Preventive strategy of flatfoot deformity using fully automated procedure

•Integrated non-invasive diagnostics to production method for low arch identification and automated customized foot orthotic design and manufacturing are developed and preliminary tests performed.•The set thresholds for foot types identification established as a part of the database development for the current study reduced the type 1 and type 2 errors to below 10.7% in comparison to previously reported above 55%.•Sedentary activity preceding to the measurements had greater effect on arch height.•Recommended test protocol — participant should not sit more than 100 min prior to the measurement, need to be applied to control this variability.•An automated algorithm is developed to translating scanned foot data into orthotic geometry, which decreases the required time of orthotic computer-aided design from over 3 h to less than 2 min. 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