On Motor Performance in Virtual 3D Object Manipulation. 2020

Alexander Kulik, and Andre Kunert, and Bernd Froehlich

Fitts's law facilitates approximate comparisons of target acquisition performance across a variety of settings. Conceptually, also the index of difficulty of 3D object manipulation with six degrees of freedom can be computed, which allows the comparison of results from different studies. Prior experiments, however, often revealed much worse performance than one would reasonably expect on this basis. We argue that this discrepancy stems from confounding variables and show how Fitts's law and related research methods can be applied to isolate and identify relevant factors of motor performance in 3D manipulation tasks. The results of a formal user study ( n=21) demonstrate competitive performance in compliance with Fitts's model and provide empirical evidence that simultaneous 3D rotation and translation can be beneficial.

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