| description abstract | Robotic technology is increasingly used for sophisticated in vitro testing designed to understand the subtleties of joint biomechanics. Typically, the joint coordinate systems in these studies are established via palpation and digitization of anatomic landmarks. We are interested in wrist mechanics in which overlying soft tissues and indistinct bony features can introduce considerable variation in landmark localization, leading to descriptions of kinematics and kinetics that may not appropriately align with the bony anatomy. In the wrist, testing is often performed using either load or displacement control with standard material testers. However, these control modes either do not consider all six degrees-of-freedom (DOF) or reflect the nonlinear mechanical properties of the wrist joint. The development of an appropriate protocol to investigate complexities of wrist mechanics would potentially advance our understanding of normal, pathological, and artificial wrist function. In this study, we report a novel methodology for using CT imaging to generate anatomically aligned coordinate systems and a new methodology for robotic testing of wrist. The methodology is demonstrated with the testing of 9 intact cadaver specimens in 24 unique directions of wrist motion to a resultant torque of 2.0 N·m. The mean orientation of the major principal axis of range of motion (ROM) envelope was oriented 12.1 ± 2.7 deg toward ulnar flexion, which was significantly different (p < 0.001) from the anatomical flexion/extension axis. The largest wrist ROM was 98 ± 9.3 deg in the direction of ulnar flexion, 15 deg ulnar from pure flexion, consistent with previous studies [1,2]. Interestingly, the radial and ulnar components of the resultant torque were the most dominant across all directions of wrist motion. The results of this study showed that we can efficiently register anatomical coordinate systems from CT imaging space to robotic test space adaptable to any cadaveric joint experiments and demonstrated a combined load-position strategy for robotic testing of wrist. | |
