Modeling the Coordinated Movements of the Head and Hand Using Differential Inverse Kinematics

Abstract

Hand reach movements for manual work, vehicle operation, and manipulation of controls are planned and guided by visual images actively captured through eye and head movements. It is hypothesized that reach movements are based on the coordination of multiple subsystems that pursue the individual goals of visual gaze and manual reach. In the present study, shared control coordination was simulated in reach movements modeled using differential inverse kinematics. An 8-DOF model represented the torso-neck-head link (visual subsystem), and a 9-DOF model represented the torsoupper limb link (manual subsystem), respectively. Joint angles were predicted in the velocity domain via a pseudo-inverse Jacobian that weighted each link for its contribution to the movement. A secondary objective function was introduced to enable both subsystems to achieve the corresponding movement goals in a coordinated manner by manipulating redundant degrees of freedom. Simulated motions were compared to motion recordings from ten subjects performing right-hand reaches in a seated posture. Joint angles were predicted with and without the contribution of the coordination function, and model accuracy was determined using the RMS error and differences in end posture angles. The results indicated that prediction accuracy was generally better when the coordination function was included. This improvement was more pronounced for low and eccentric targets, as they required greater contribution of the joints shared by both visual and manual subsystems.