A chord-angle-based approach with expandable solution space to 1-degree-of-freedom (DOF) rehabilitation mechanism synthesis

Abstract

Abstract. Rehabilitation robots have been proven to be an effective tool for patient motor recovery in clinical medicine. Recently, few degrees of freedom (DOFs), especially 1-DOF, rehabilitation robots have drawn increasing attention as the complexity and cost of the control system would be significantly reduced. In this paper, the mechanism synthesis problem of 1-DOF rehabilitation robots is studied. Traditional synthesis methods usually aim at minimizing the trajectory error to generate a mathematically optimal solution, which may not be a practically feasible solution in terms of engineering constraints. Therefore, we propose a novel mechanism synthesis approach based on chord angle descriptor (CAD) and error tolerance expansion to generate a pool of mechanism solutions from which mathematically and practically optimal solutions can be selected. CAD is utilized for its capability to represent the same-shaped trajectories of different mechanisms in a unified way, and it is robust to the noise in the rehabilitation trajectory acquired by motion capture systems. Then a library of mechanism trajectories is established with compressed representations of CAD via an auto-encoder algorithm to speed up the matching between mechanism and rehabilitation trajectory where the matching error tolerance can be adjusted according to practical rehabilitation specifications. Finally, a design example of a 1-DOF rehabilitation robot for upper-limb training is provided to demonstrate the efficacy of our novel approach.