Extending Fitts' Law to manual obstacle avoidance.

In this study we asked whether Fitts' Law, a well-established relationship that predicts movement times (MTs) for direct movements between two positions, could be extended to predict MTs for curved, obstacle avoiding, movements. We had participants make movements in the presence of an obstacle. Using these data, we tested an extensions of Fitts' Law that predicted MTs based on the movement's index of difficulty and the distance that the obstacle intruded into the direct movement path. Including both factors led to more accurate predictions of MTs for obstacle-avoiding movements than was possible with the index of difficulty alone. In addition, the simple extension of Fitts' Law did as well as a model which relied on the obtained movement paths between targets. This is an encouraging outcome because it suggests that the physical layout of the workspace can be used to predict MTs for obstacle avoiding movements, an accomplishment that fits with the spirit of Fitts' Law.