Identifying and comparing states of time-delayed systems: phase diagrams and applications to human motor control systems

A data driven characterization of time-delayed stochastic systems is proposed in terms of linear delay differential equations and two drift parameters. It is shown how these parameters determine the states of such systems with respect to generalized phase diagrams. This approach allows for a comparison of systems with different parameters as exemplified for two motor control tasks: tracking and force production.