Human-machine interaction (HMI) can be modeled as information flows through bidirectional communication channels, where the human receives sensory information from the machine and sends command information back to the machine. The interaction between human and machine can thus be characterized by the dynamics of information exchange measured in bits per second (b/s).
The information-transmission rate (ITR) from human to machine is expected to depend on the complexity of the machine dynamics as well as human capabilities and limitations. We propose to investigate this dependency quantitatively in order to provide a measure of human performance. The HMI task considered in our investigation is a one-dimensional manual control task of an unstable system. A set of experiments are conducted where the human subjects maneuver a joystick in order to stabilize an inverted pendulum simulation. Two scenarios are analyzed: when time delay affects the feedback control system, and when the degree of instability of the task is increased.
Using information- and control-theoretic approaches we identify the lower bound for the ITR of the controller, which is dependent on the dynamics of the control task. From time series analysis, we suggest a method for ITR estimation from human experiments. We believe that the difference between these two quantities allows for assessment of human performance and for the prediction of its limitations. Additionally, the association between the recorded ITR and the bandwidth of the controller will be discussed in order to create a more complete picture of human manual control abilities and limitations
