EMG-based energy expenditure optimization for active prosthetic leg tuning.

Abstract

In recent years, active prosthetic legs have been developed and deployed commercially that help amputees to initiate gait with less effort and more symmetry in the pattern. However, the process of initial set up and tuning is highly time and cost consuming. It requires prosthetic experts to observe the gait and the feedback from amputees to manually tune the parameters subjectively. In this study, an electromyography (EMG)-based energy expenditure optimization method was presented to automatically tune the prosthetic limb. For this purpose, a wide variety of lower body muscles were observed and the energy expenditure was modeled based on their electrical activity. The tuning optimization was implemented based on a grid-searching protocol designed in this study. This method resulted in a power value comparable to manual tuning, which provided enough force to facilitate gait for amputees. This study shows the feasibility of automatic tuning and removal of the need for referral to an expert.