Detecting simulated sprained ankle plantar pressure pattern using artificial neural network

Ankle sprains are one of the most common injuries during sport activities. Gait impairment is a significant problem in ankle sprained cases, leading to decreased activity and limitations in function. The importance of early assessment of sprained ankle is clear. The goal of this early assessment is to start early treatment that can limit the necessary time of rest for the patient. Limiting the rest time is very important specially for an injured athlete who wants to decrease the time lost in practice. The aim of the current study was first, to simulate the pressure distribution under the normal foot and an ankle sprained foot, and second, using artificial neural networks for classifying the normal and the simulated sprained ankle plantar pressure patterns.