Design and Operation Methodologies for Upper-Limb Exoskeletons

Upper limb motor impairments affect millions of individuals worldwide, with stroke survivors experiencing persistent functional limitations that reduce independence in daily activities. Despite advances in rehabilitation robotics, current technologies face key limitations: predominantly single-joint assistance that does not preserve natural coordination patterns, configuration-dependent force measurement in cable-driven systems, and the lack of systematic design frameworks integrating biomechanical and engineering requirements. This dissertation presents a systematic design methodology for upper limb rehabilitation exoskeletons, validated through the development of a coordinated shoulder-elbow cable-driven exosuit. The methodology integrates Product Design Specifications (PDS), Multi-Criteria Decision Making (MCDM), mathematical modeling, and iterative validation. Its application to a three-degree-of-freedom case study demonstrates structured exploration of design alternatives and traceable decision-making. The proposed exosuit introduces a motor-proximal sensing architecture, relocating force measurement from cable anchor points to actuation units. This enables coordinated multi-joint assistance across shoulder and elbow movements while preserving functional range of motion. The approach addresses the trade-off between measurement accuracy and operational workspace typical of cable-driven systems. Experimental validation with human subjects (n=5) shows reduced muscle activation during assisted movements, preservation of natural kinematic coordination, and reliable force sensing. The system achieves a total mass of 3.3 kg, supporting portable and self-wearable use. A complementary camera-based validation method enables accessible performance assessment, particularly in resource-constrained settings. These contributions demonstrate how a systematic design methodology, combined with enabling technological solutions, can address key challenges in multi-joint coordination, sensing reliability, and reproducible development in rehabilitation robotics.