Foot-surface-structure analysis using a smartphone-based 3D foot scanner

Abstract

A thorough understanding of the influence of the foot skeletal structure on hallux valgus (HV) is required for HV prevention. We developed a system using a 3D foot scanner on a smartphone to clarify the relationships between foot features and HV risk. Two-dimensional video images were recorded on a smartphone, sent to a computer or cloud server, and used to construct a 3D foot-feature model, considering 10 foot features associated with HV. The participants (419 individuals, aged 40-89 years) stood with their toes 12cm apart and heels 8cm apart during video recording. The height and weight were measured for body-mass index calculation. Age-dependent foot-feature variations were observed slightly for males and distinctively for females. For females, the great toe-first metatarsal head-heel (GFH) angle associated with HV increased with age, i.e., the GFH angle increased with age, suggesting that HV increased with age. Multiple regression analysis revealed that the features determining the GFH angle are the second toe-heel-navicular angle, bone distance axis, and transverse arch length and height. The adjusted coefficients of determination were 0.54 and 0.52 for males and females, respectively. This approach enables simple foot structure assessment for HV risk evaluation.