The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to improve modeling and treatment for various disorders. The initial application is to personalize footwear. This project uses a smartphone camera to determine the size and orientation of feet and gait. It combines computer vision, image processing, machine learning, material science, and anatomy and physiology to develop a virtual solution to fit shoes. This enables a new low-cost method for evaluating physiological conditions with potentially straightforward consumer solutions. This project supports a novel data-analytics solution that provides accurate footwear recommendations based on static foot shape and dynamic foot function, using only a smartphone to capture images. This project will develop the algorithms using machine learning and statistical modeling for a user to evaluate the potential utility of a comfortable shoe. This project will evaluate the prediction accuracy of a prototype system.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
