Studying human motor control has received increased attention during the past decades. Both the design and control of robotic artifacts may benefit from observation of human behavior. In this paper a novel method for capturing the dynamic behavior of the human hand is presented. The low dimensional kinematics of the human hand, including the wrist, and the low dimensional representation of the muscular activations were correlated through a linear time invariant (LTI) state space model. A linear output regulation controller was used in order to drive a simulated hand and the resulting trajectories were compared with the experimentally captured trajectories.