For stroke patients with upper limb motor dysfunction, rehabilitation training with the help of rehabilitation robots is a social development trend. Existing upper limb rehabilitation robots have difficulty fully fitting the complex motion of the human shoulder joint and have poor human–robot compatibility. In this paper, based on the anatomical structure of the human upper limb, an equivalent mechanism model of the human upper limb is established. The configuration synthesis of the upper limb rehabilitation mechanism was carried out, a variety of shoulder joint man–machine closed-chain Θ_s and shoulder elbow human–machine closed-chain Θ_se configuration combinations were synthesized, and the configuration model with compatibility and reduced moment conduction attenuation was selected from them. Two configurations, 2P_a1P3R_a and 5R_a1P, are proposed for the generalized shoulder joint mechanism of the robot. The closed-chain kinematic models of the two configurations are established, and the velocity Jacobian matrix is obtained. Motion performance analysis, condition reciprocal analysis and operability ellipsoid analysis of different configuration design schemes were carried out in different operation planes. The results show that in the normal upper limb posture of the human body, the 5R_a1P configuration of the shoulder joint has better kinematic performance. Finally, on this basis, an upper limb rehabilitation robot prototype with good human–computer compatibility is developed, and its moving space was verified.

The lower limb rehabilitation robot is a typical man-machine coupling system. Aiming at the problems of insufficient physiological information and unsatisfactory safety performance in the compliance control strategy for the lower limb rehabilitation robot during passive training, this study developed a surface electromyography-based gain-tuned compliance control (EGCC) strategy for the lower limb rehabilitation robot. First, the mapping function relationship between the normalized surface electromyography (sEMG) signal and the gain parameter was established and an overall EGCC strategy proposed. Next, the EGCC strategy without sEMG information was simulated and analyzed. The effects of the impedance control parameters on the position correction amount were studied, and the change rules of the robot end trajectory, man-machine contact force, and position correction amount analyzed in different training modes. Then, the sEMG signal acquisition and feature analysis of target muscle groups under different training modes were carried out. Finally, based on the lower limb rehabilitation robot control system, the influence of normalized sEMG threshold on the robot end trajectory and gain parameters under different training modes was experimentally studied. The simulation and experimental results show that the adoption of the EGCC strategy can significantly enhance the compliance of the robot end-effector by detecting the sEMG signal and improve the safety of the robot in different training modes, indicating the EGCC strategy has good application prospects in the rehabilitation robot field.

Aiming at solving the problems of low compliance and unsatisfactory therapeutic effect in most existing waist rehabilitation robots, this letter presents a compact waist rehabilitation robot (CWRR) for patients with low back pain (LBP). First, the CWRR with a rigid pose adjustment mechanism and a soft curvature adjustment mechanism is designed to adapt to the waist movement and adjust lumbar curvature. Then, the kinematic analysis was conducted using the closed-loop vector method and the phenomenological theory model. Finally, unit mechanism tests and a comprehensive prototype test were carried out to validate the rationality of the theoretical models and the adaptability and compliance of the CWRR. The CWRR adjusted the curvature angle within the range of 10–60 degrees with small errors. Under different pose and curvature conditions, the man-machine contact pressure was lower or slightly higher than the low-pressure regime threshold (10 kPa). Experimental results show that the CWRR possesses potential clinical applications for patients with LBP disease and can provide theoretical and technical reserves for the research and development of curvature-adjustment waist rehabilitation robots.

For rehabilitation therapy robots, the movement range, and comfort of rehabilitation are crucial to the patient’s training and recovery and are also key factors in the design and performance evaluation of rehabilitation robots. In this paper, a highly harmonized upper extremity rehabilitation robot was proposed based on the human-machine coupling system model. Meanwhile, the shoulder joint structure of the rehabilitation robot was optimized to study the workspace range of this robot, the workspace of the upper extremity rehabilitation robot was fitted based on kinematic equations and the workspace volume size for different shoulder joint angles was analyzed. Finally, the upper extremity exoskeleton rehabilitation robot prototype was used to conduct the movement range tracking experiment and human-machine compatibility experiment in healthy volunteers to verify the rehabilitation training range and movement comfort of the rehabilitation robot. The experimental results show that when the optimized upper extremity exoskeleton rehabilitation robot was used to move in the coronal plane and sagittal plane of the human body, the overlaps of the movement range of the upper extremity wrist point W and the movement range of the healthy person was 97.23% and 97.66%, respectively, while the human-machine interaction force generated during the movement was mainly concentrated in the range of 0–10 kPa, which belongs to the low-pressure range of human-machine interaction. Therefore, this upper extremity rehabilitation robot can increase the movement range of patients’ upper extremities and improve the comfort of rehabilitation training.