Intermittent control as a model of mouse movements

TL;DR

This paper introduces Intermittent Control models as a new way to simulate human mouse movements, showing they better replicate observed behaviors than continuous control models, and providing insights into variability in HCI tasks.

Contribution

The paper develops and validates Intermittent Control models for human mouse movements, demonstrating improved generative ability over continuous models and aligning with psychological theories.

Findings

IC better reproduces movement variability

IC models outperform continuous control models

Provides physiological and psychological insights

Abstract

We present Intermittent Control (IC) models as a candidate framework for modelling human input movements in Human--Computer Interaction (HCI). IC differs from continuous control in that users are not assumed to use feedback to adjust their movements continuously, but only when the difference between the observed pointer position and predicted pointer positions become large. We use a parameter optimisation approach to identify the parameters of an intermittent controller from experimental data, where users performed one-dimensional mouse movements in a reciprocal pointing task. Compared to previous published work with continuous control models, based on the Kullback-Leibler divergence from the experimental observations, IC is better able to generatively reproduce the distinctive dynamical features and variability of the pointing task across participants and over repeated tasks. IC is compatible with current physiological and psychological theory and provides insight into the source of variability in HCI tasks.