Artificial neural networks in the selection of shoe lasts for people with mild diabetes.

This research addressed the selection of shoe lasts for footwear design to help relieve the pain associated with diabetic neuropathy and foot ulcers. A reverse engineering (RE) technique was used to convert point clouds corresponding to scanned shoe lasts and diabetic foot data into stereo lithograph (STL) meshes. A slicing algorithm was developed and was used to find relevant girth features of diabetic foot and the shoe lasts.