title: Gait simulation via a 6-DOF parallel robot with iterative learning control.
abstract: We have developed a robotic gait simulator (RGS) by leveraging a 6-degree of freedom parallel robot, with the goal of overcoming three significant challenges of gait simulation, including: 1) operating at near physiologically correct velocities; 2) inputting full scale ground reaction forces; and 3) simulating motion in all three planes (sagittal, coronal and transverse). The robot will eventually be employed with cadaveric specimens, but as a means of exploring the capability of the system, we have first used it with a prosthetic foot. Gait data were recorded from one transtibial amputee using a motion analysis system and force plate. Using the same prosthetic foot as the subject, the RGS accurately reproduced the recorded kinematics and kinetics and the appropriate vertical ground reaction force was realized with a proportional iterative learning controller. After six gait iterations the controller reduced the root mean square (RMS) error between the simulated and in situ; vertical ground reaction force to 35 N during a 1.5 s simulation of the stance phase of gait with a prosthetic foot. This paper addresses the design, methodology and validation of the novel RGS.
authors.affiliation: VA RR&D Center of Excellence for Limb Loss Prevention and Prosthetic Engineering, VA Puget Sound Health Care System, Seattle, WA 98108, USA. paubin@u.washington.edu
authors.forename: Patrick M
authors.initials: PM
authors.lastname: Aubin
authors.forename: Matthew S
authors.initials: MS
authors.lastname: Cowley
authors.forename: William R
authors.initials: WR
authors.lastname: Ledoux
mesh_terms: D001185:Artificial Intelligence; D032701:Biomimetics / Q000379:methods*; D003198:Computer Simulation; D005684:Gait / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D012371:Robotics / Q000379:methods*