Automatic Measurement of Neutral Foot Posture Using Three-Dimensional Scanning

Abstract

The Rearfoot Angle (RFA) is the most commonly method used for foot posture assessment, and it is also a method for evaluating the subtalar joint neutral foot posture. However, orthopedists and researchers often meet trouble for the measurements of the RFA and neutral foot posture due to lacking measurement with automation and objectivity. In general, the RFA was measured using a goniometer to align with manual markers on the foot. The purpose of this study implements the automatic computing of leg angle, foot angle, and RFA by the foot model using Three-Dimensional (3D) scanning. This study contributes to the algorithms to The purpose of this study implement the automatic and objective computing of leg angle, foot angle, and RFA by the foot model using 3D scanning. The automatic calculation on leg angle, foot angle, and neutral foot posture has been created, test, and validated completely in this study. There are two algorithm methods proposed to determine the midpoint on the leg or foot outline. The midline has been computed by linear regression through five midpoints. The leg and foot angles are calculated by the tibial and calcaneal midlines, respectively. Through the subject standing on eversion foot platforms, the neutral posture of the foot can be computed by the leg and foot angles determined by the 3D model scanned of the foot with various tilt angles. The determinations of the midpoint and midline have been demonstrated algorithm by MATLAB. Based on comparing with the goniometer measured, selecting the midpoint algorithm of the limit points and the lowest point methods to determine the tibial and calcaneal midlines respectively would carry out better results. The foot 3D scanning measurement proposed in this study has been tested and validated from the goniometer. This study can determine the leg angle, foot angle, and neutral foot postures for a subject with normal weight status, but be not suitable for that with obese weight status. In the future, this study can provide guidance for foot posture assessment and personal insoles design.

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