Reducing Gait Asymmetry in Transfemoral Amputees — A Neural Network-Based Approach

Abstract

Gait asymmetry between intact and prosthetic limbs is one of the factors that affect the long-term health of an amputee. Existing prosthetic devices have fixed controllers that cannot adapt to changes in user gait, thereby contributing to this asymmetry. In this paper, we use the stance period of both limbs to measure the asymmetry in gait. We propose a neural network-based control strategy that can adapt to changing gait in real time and help achieve near-natural gait.