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.