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.
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