As gesture interfaces become more main-stream, it is increasingly important to investigate the behavioral characteristics of these interactions – particularly in three-dimensional (3D) space. In this study, Fitts’ method was extended to such input technologies, and the applicability of Fitts’ law to gesture-based interactions was examined. The experiment included three gesture-based input devices that utilize different techniques to capture user movement, and compared them to conventional input technologies like touchscreen and mouse. Participants completed a target-acquisition test and were instructed to move a cursor from a home location to a spherical target as quickly and accurately as possible. Three distances and three target sizes were tested six times in a randomized order for all input devices. A total of 81 participants completed all tasks. Movement time, error rate, and throughput were calculated for each input technology. Results showed that the mean movement time was highly correlated with the target's index of difficulty for all devices, providing evidence that Fitts’ law can be extended and applied to gesture-based devices. Throughputs were found to be significantly lower for the gesture-based devices compared to mouse and touchscreen, and as the index of difficulty increased, the movement time increased significantly more for these gesture technologies. Error counts were statistically higher for all gesture-based input technologies compared to mouse. In addition, error counts for all inputs were highly correlated with target width, but little impact was shown by movement distance. Overall, the findings suggest that gesture-based devices can be characterized by Fitts’ law in a similar fashion to conventional 1D or 2D devices.

This paper describes a novel method for displaying data obtained by three-dimensional medical imaging, by which the position and orientation of a freely movable screen are optically tracked and used in real time to select the current slice from the data set for presentation. With this method, which we call a “freely moving in-situ medical image”, the screen and imaged data are registered to a common coordinate system in space external to the user, at adjustable scale, and are available for free exploration. The three-dimensional image data occupy empty space, as if an invisible patient is being sliced by the moving screen. A behavioral study using real computed tomography lung vessel data established the superiority of the in situ display over a control condition with the same free exploration, but displaying data on a fixed screen (ex situ), with respect to accuracy in the task of tracing along a vessel and reporting spatial relations between vessel structures. A “freely moving in-situ medical image” display appears from these measures to promote spatial navigation and understanding of medical data.