Toe gaps and their assessment in footwear for people with diabetes: a narrative review

Background Adequate footwear fit is critical in preventing diabetes-related foot ulcers. One important element is the toe gap, the difference between foot length and internal footwear length available to the foot. We summarised the literature on toe gaps in studies assessing footwear worn by people with diabetes, the methods used to measure both foot length and internal footwear length and identify ambiguities which may impact on toe gap assessment in clinical practice, and suggest pragmatic solutions. Methods The Google Scholar database was searched to April 2020 for peer-reviewed studies using keywords related to incorrectly fitting or ill-fitting and diabetes, foot and ulcer which returned 979 results. Included studies within this narrative review encompassed toe gap measurement to assess footwear worn by people with diabetes. Results A total of eight studies were included after full paper review. Toe gap ranges as used in assessments of footwear worn by people with diabetes vary, with a minimum of 1.0–1.6 cm and a maximum of 1.5–2.0 cm, as do methods of measuring internal footwear length. Only three published studies suggested possible measuring devices. Conclusions Toe gap ranged as used when assessing footwear fit in people with diabetes vary and a gold standard device for internal footwear length measurement has yet to emerge. International guidelines provide welcome standardisation, but further research is needed to evaluate both the effect of toe gap ranges upon pressure, plantar stress response and ulceration and available measuring devices to facilitate development of toe gap measurement protocols that may further enhance consistency in practical assessments.

Footprint Curvature in Spanish Women: Implications for Footwear Fit

The incorrect adjustment of footwear produces alterations in the foot that affect quality of life. The usual measurements for shoe design are lengths, widths and girths, but these measures are insufficient. The foot presents an angle between the forefoot and the rearfoot in the transverse plane, which is associated with foot pronation, hallux valgus and metatarsus adductus. Here, we aimed at identifying the groups formed by the angulations between the forefoot and rearfoot using a sample of footprints from 102 Spanish women. The angle between the forefoot and rearfoot was measured according to the method described by Bunch. A cluster analysis was performed using the K-means algorithm. Footprints were grouped into three types: curved, semi-curved and straight, according to the degrees of angulation between the forefoot and rearfoot. There is great variability in the morphology of the foot. Based on our findings, to achieve a better footwear fit, we propose the manufacture of three types of lasts with different curvatures.

Foot Depth Map Point Cloud Completion using Deep Learning with Residual Blocks

Fit is extremely important in footwear as fit largely determines performanceand comfort. Current footwear fit estimation mainly usesonly shoe size, which is extremely limited in characterizing theshape of a foot or the shape of a shoe. 3D scanning presents asolution to this, where a foot shape can be captured and virtuallyfit with shoe models. Traditional 3D scanning techniques have theirown complications however, stemming from their need to collectviews covering all aspects of an object. In this work we explore adeep learning technique to compete a foot scan point cloud frominformation contained in a single depth map view. We examine thebenefits of implementing residual blocks in architectures for this application,and find that they can improve accuracies while reducingmodel size and training time.