Toward improved understanding of foot shape, foot posture, and foot biomechanics during running: A narrative review - Mei, Qichang; Kim, Hyun Kyung; Xiang, Liangliang; Shim, Vickie; Wang, Alan; Baker, Julien S.; Gu, Yaodong; Fernandez, Justin (Frontiers in Physiology, 2022)
Current narrative review has explored known associations between foot shape, posture, and foot conditions during running. The arch index was found as a useful metric of foot posture but less useful in developing and obese individuals. Care shall be taken when using foot posture index to associate pronation with injury risk, and Achilles Tendon angle and longitudinal arch angle is needed to elucidate risk. Statistical shape modelling (SSM) may derive learnt information from population-based inference and fill in missing data from personalised information. Bone shapes and tissue morphology have been associated with pathology, gender, age, and height and may develop rapid population-specific foot classifiers. Based on this review, future studies are suggested to conduct around, 1) tracking the internal multi-segmental foot motion and mapping the biplanar 2D motion to 3D shape motion with SSM; 2) implementing multivariate machine learning or convolutional neural network to address non-linear correlations in foot mechanics with shape or posture; 3) standardizing wearable data for rapid prediction of instant mechanics, load accumulation, injury risks and adaptation in foot tissue and bones, and correlation with shapes; 4) analysing dynamic shape and posture via marker-less and real-time techniques under real-life scenarios for precise evaluation of clinical foot conditions and performance-fit footwear development.