Design and optimization of PARTNER: A parallel actuated robotic trainer for NEuroRehabilitation

Abstract

Robotic devices are a promising and dynamic tool in the realm of post-stroke rehabilitation. Researchers are still investigating how the use of robots affects motor learning and what design characteristics best encourage recovery. We present a parallel-actuated, end-effector robot designed to provide spatial assistance for upper-limb therapy while exhibiting low impedance and high backdrivability. A gradient based optimization was performed to find an optimal design that accounted for force isotropy, mechanical advantage, workspace size, and counter-balancing. A beta prototype has been built to these specifications (low impedance and high backdrivability) and has undergone initial controller performance as well as fit and function testing. By fitting a nonlinear model to experimental frequency response data, the apparent mass, viscous friction coefficient, and dynamic dry friction coefficient were determined to be 0.242 kg, 0.114 Ns/m, and 0.894 N respectively. The robot will serve as a testing platform to investigate motor learning and evaluate the efficacy of control schemes for post-stroke movement therapy.

Dynamic Modeling and Interactive Performance of PARM: A Parallel Upper-Limb Rehabilitation Robot Using Impedance Control for Patients after Stroke

“…More importantly, as the end-effector is controlled in parallel, the errors of the joint control are not accumulated and amplified by serial counterparts, and thus the manipulator is less affected by joint clearance and has higher precision in aspects of position, stiffness, and interactive force control [ 12 ]. Therefore, parallel manipulators have been recently applied to rehabilitation robots, including shoulder [ 12 , 24 ], wrist [ 25 ], hip [ 26 ], and upper-limb rehabilitation devices [ 27 ].…”