Meeting Abstract
A Neuromuscular Approach to Powered Prosthetic Controllers By: Isaac Romero, Jeremy Petak, Uzma Tahir, John Tester, and Kiisa Nishikawa The BiOM is a powered foot-ankle prosthesis that allows users a more human like walking experience. The commercially available BiOM controller uses a state based control algorithm to command the required torque at the ankle. However, this approach requires optimization to specific walking conditions, such as level walking or stair ambulation. In order to mimic robust human walking on a variety of terrains, we used a bio-inspired model based on muscle physiology to compute ankle torque. Hill-type muscle models, based on the sliding filament theory, are unable to account for intrinsic muscle properties. A new theory of muscle contraction, called the winding filament hypothesis (WFH), predicts muscle force during dynamic conditions and was incorporated into the BiOM controller. The winding filament model consists of a titin spring and a series tendon spring, a contractile element, a damper, and a pulley. The human lower limb is modeled as a hinge at the ankle joint, with anterior and posterior muscle groups that dorsiflex and plantarflex, respectively. The BiOM’s internal sensor measures ankle angle, which is then converted to virtual muscle length to determine anterior and posterior muscle force based on the force-length and force-velocity relationship of muscles, and the WFH. By using parameters such as damping and spring constants that are subject specific, and muscle activation patterns that resemble biological muscles, we were able to command net ankle torque matching intact subjects. Control algorithms for powered prostheses will allow robust control, adapting to changing environments and terrains, increasing freedom for users.
