Enhancing Human–Robot Compatibility in Shoulder Exoskeletons: Passive Joint Optimization of PPRRRP vs. RRRUP Configurations

This study aims to evaluate the kinematic performance of two shoulder rehabilitation exoskeleton configurations to address the critical challenge of human–robot compatibility. Utilizing Hunt’s mobility formula and task-specific Jacobian analysis, we developed a closed-chain kinematic model integrating transient glenohumeral joint dynamics, validated through force/torque measurements and ANOVA statistical comparisons. The PPRRRP configuration, featuring orthogonally distributed passive prismatic joints, demonstrated superior performance: 40–60% lower interaction forces (F¯total=2.66 N), near-isotropic manipulability (ellipsoid axis ratio < 1.5), and 60% reduced operational torque (T¯total=0.18 N·m) compared to RRRUP’s universal joint design. These results establish passive DOF optimization as a viable alternative to actuator-dense systems, diverging from conventional approaches like ARMin-III that prioritize active control. The originality lies in bridging theoretical configuration synthesis with empirical validation, offering a replicable framework for compatibility assessment. This work advances rehabilitation robotics by demonstrating that mechanical transparency—achieved through strategic passive joint allocation—enhances natural movement synergy without compromising stability, proposing hypotheses on energy efficiency and isotropy–fatigue correlations for future exploration. Clinical translation and adaptive impedance control integration are identified as critical next steps to optimize patient-specific rehabilitation outcomes.