With the increasing number of stroke patients, there is a growing demand for lower-limb rehabilitation exoskeletons. While current mechanisms are preferred for their light weight and dexterous design in limited environments, the alignment of the structures and motion are still not matched perfectly to human movements. This study develops a novel structure and configuration optimization method for knee part rehabilitation with special passive self-alignment modules. The driving segment is mechanically coupled to the patients’ lower limb. All components are designed with high rigidity and fully constrained to ensure smooth and continuous motion. Then, the kinematics are systematically derived to establish the foundation for the control system. Next, the application of the particle swarm optimization algorithm determines the optimal parameters for each revolute joint during the bending motion, and reduces the non-ideal S-shaped motion deformation curve caused by the offset of the joint rotation center and the load at the end effector successfully. The final results demonstrate that the optimized SRE achieves 97.5% motion accuracy under large-angle knee movement. This work presents simulation-only validation, and clinical testing remains future work. The proposed mechanism provides a promising solution for post-stroke rehabilitation, and is also applicable to geriatric lower-limb weakness and orthopedic postoperative recovery.
Gao et al. (Wed,) studied this question.