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We present Intermittent Control (IC) models as a candidate framework formodelling human input movements in Human--Computer Interaction (HCI). ICdiffers from continuous control in that users are not assumed to use feedbackto adjust their movements continuously, but only when the difference betweenthe observed pointer position and predicted pointer positions become large. Weuse a parameter optimisation approach to identify the parameters of anintermittent controller from experimental data, where users performedone-dimensional mouse movements in a reciprocal pointing task. Compared toprevious published work with continuous control models, based on theKullback-Leibler divergence from the experimental observations, IC is betterable to generatively reproduce the distinctive dynamical features andvariability of the pointing task across participants and over repeated tasks.IC is compatible with current physiological and psychological theory andprovides insight into the source of variability in HCI tasks.

Intermittent control as a model of mouse movements