The personalization of stiffness for an ankle-foot prosthesis emulator using Human-in-the-loop optimization

Abstract

Evidence suggests that the metabolic cost associated with the locomotive activity of walking is dependent upon ankle stiffness. This stiffness can be a control parameter in an ankle-foot prosthesis. Considering unique physical interaction between each individual with below-knee amputation and robotic ankle-foot prosthesis, individually tuned stiffness in a robotic ankle-foot prosthesis may improve assistance benefits. This personalization can be accomplished through human-in-the-loop (HIL) Bayesian optimization (BO). Here, we conducted a pilot study to identify personalized ankle- foot prosthesis stiffness using the HIL BO to minimize the cost of walking, shown by metabolic cost. We used an improved versatile ankle-foot prosthesis emulator, which enabled to test controllers with a wide range of stiffness conditions. Two participants with simulated amputation reduced their cost of walking under the condition of personalized (optimized) stiffness by 6% and 5%, respectively. This result suggests that personalized stiffness may improve assistance benefit.