Design of Multi-Mode RSCR Mechanism and Its Application in Gait Rehabilitation

Planar single degree-of-freedom (DOF) mechanisms have been widely utilized in human rehabilitation devices, yet research on spatial single-DOF mechanisms remains relatively limited. Given that natural human motion often involves complex spatial characteristics, this study addresses this gap by proposing a multi-mode spatial RSCR mechanism for gait rehabilitation. A multi-mode mechanism incorporates adjustable parameters, allowing the structure to be tuned to fit different task trajectories by modifying these parameters. The kinematic model of the mechanism is derived and a circuit analysis is performed on the basis of this model to ensure the accuracy of the trajectory synthesis. Using Gaussian Mixture Model (GMM) clustering, a dataset of human gait trajectories is grouped into three clusters, and a representative trajectory is regressed for each cluster as the target trajectory. A two-stage optimization approach is employed: multi-objective optimization via adaptive-reference-point-based nondominated sorting genetic algorithm (ANSGA-III}) identifies the optimal adjustable parameters (yA and yFc), while single-objective optimization through GA-BFGS determines the specific adjustment values and other parameters of the mechanism. Dual-parameter adjustment significantly improves the mechanism's ability to adapt to various gait trajectories, achieving subcentimeter precision in certain cases. This work explores a viable path for the development of spatial rehabilitation mechanisms and highlights potential advancements in the multi-mode design of gait rehabilitation systems.