The robotic gait simulator: a dynamic cadaveric foot and ankle model for biomechanics research

Abstract

Background. Lower limb dynamic cadaveric gait simulators are useful for investigating the biomechanics of the foot and ankle but many systems have several common limitations, including: simplified tendon forces, non-physiologic tibial kinematics, greatly reduced velocities, scaled body weight (BW), and trial-and-error vertical ground reaction force (vGRF) control. The objective of this dissertation is to design, develop, and validate a robotic gait simulator (RGS) which addresses these limitations. As a powerful tool for clinical research we further aim to use the RGS to: 1) evaluate biomedical devices (including prosthetic feet); 2) model normal and pathological gait; 3) evaluate surgical treatment strategies; 4) elucidate disease etiology; and 5) determine biological function. Methods. A 6-degress of freedom (6-DOF) parallel robot was utilized as part of the RGS to recreate the relative tibia to ground motion. A custom-designed nine-axis proportional-integral-derivative (PID) force control tendon actuation system provided force to the extrinsic tendons of the cadaveric lower limb. A fuzzy logic vGRF controller was developed which altered the target tibialis anterior and Achilles tendon force in real time, and iteratively adjusted the robotic trajectory in order to track a target vGRF. Results. The RGS was able to accurately reproduce 6-DOF tibial kinematics, tendon forces, and vGRF with a cadaveric lower limb. The fuzzy logic vGRF controller was able to track the target in vivo vGRF with an average root mean square (RMS) error of only 5.9% BW during a biomechanically realistic (¾ BW, 2.7 s) stance phase simulation. The five objectives that motivated the development of the RGS were achieved through five clinical studies which simulated: 1) transtibial amputee gait; 2) a flat foot deformity, 3) arthrodesis of the first metatarsophalangeal joint; 4) a long second metatarsal and its relationship to the crossover toe deformity, and 5) normal foot and ankle kinematics. Conclusion. By leveraging robotic technologies and advanced intelligent control methods the RGS represents the state of the art in dynamic cadaveric gait simulation and has demonstrated its value as a clinical research tool.