Abstract
Design of an upper-arm exoskeleton requires knowledge of human operational ranges and workspace distributions. Motion capture recordings of right-arm motion during common tasks, known as activities of daily living (ADLs), are taken to represent a plausible workspace for an exoskeleton. An inverse kinematic model of BLUE SABINO (BiLateral Upper-extremity Exoskeleton for Simultaneous Assessment of Biomechanical and Neuromuscular Output), driven by ADL data is established to map right-arm joint locations to exoskeleton motor joint space. A kinematic representation of a human right-arm driven by ADL data is implemented via a vector analysis utilizing quaternion rotation/translation and used to visualize ADL recordings. A model of the BLUE SABINO exoskeleton whose motion is driven by the mapped motorjoint-space data is used to validate the mapping graphically. The available ADL database is mapped to motor joint space. Motor position distributions are generated from the resulting dataset and estimates of robot range of motion, (ROM) and statistics for shoulder motor positions are established. A kinematically and inertially accurate model of the BLUE SABINO is developed by exporting SolidWorksOR part models into SimScape Multibody (MathWorks). The model is used to produce operational torque estimates for shoulder motors. Initial simulations indicate that the motors of interest have been properly sized.