Estimation of kinematics parameters dependent on pronation supination for modeling forearm skeletal system based on CT images

In the disease developing mechanism of baseball elbow, it is believed that there is a need to understand the skeletal system of the elbow joint and forearm. Focusing on the interior of a elbow joint, the humerus, ulna and radius are constituted a complex structure covered with soft tissue, such as the joint capsule and collateral ligaments. In order to clarify the failure of the forearm, Kecskemethy et al., considered a simple forearm skeleton model. Although they estimated ulnar behavior by adjusting the stiffness of the model, Nojiri et al. proposed a method for estimating the link length and the measurement error gain using the steepest descent method (SDM) as another approach. However, since the least squares method (LSM) has a possibility of falling into a local solution; hence, in this paper, we propose a method for estimating in Particle Swarm Optimization (PSO). In addition, by estimating the link length and the measurement error gain that made dependent on the pronation supination (pro-/supination) posture, we indicate that was able to carry out the reduction of estimation error.