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Abstract

Understanding human cursor tracking behavior is essential in understanding human motor control. Though tracking has been hypothesized as a sequence of discrete movements, better data is needed to support the theory. By analyzing moment-to-moment tracking data, this paper shows that discrete, non-ballistic movements exist throughout a tracking task, and that these short submovements can be characterized by either Fitts’ law or a linear model. A cognitive model was built to incorporate the characteristics of these discrete movements into a dual task. Using parameters estimated through linear regression of the movement data, the model achieves a good fit to the overall performance measures of the dual-task experiment. This research investigates the characteristics of human motor control in tracking tasks, improves modeling techniques by providing a new method for estimating tracking parameters, and advances the science of motor control with new evidence for the discrete movement tracking hypothesis. The discrete movement model presented here offers an excellent alternative to established control theory models that are used to simulate steering in cognitive models of driving.

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A Discrete Movement Model for Cursor Tracking Validated in the Context of a Dual-Task Experiment

Abstract

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