Fitts's Law has been used extensively in HCI to describe 2D targeting; however, the controlled tasks generally used neglect aspects of real-world pointing, including how the intended use of a target affects its acquisition. We studied aiming to a target in four tasks requiring varying precision after acquisition. Our results present the first evidence that the intended use of a target affects its acquisition in terms of movement time and motion kinematics for computer aiming. Important for researchers who model 2D targeting, our results also have particular impact for HCI research that uses motion kinematics.

Prior work on physiological game interaction has focused on dynamically adapting games using physiological sensors. In this paper, we propose a classification of direct and indirect physiological sensor input to augment traditional game control. To find out which sensors work best for which game mechanics, we conducted a mixed-methods study using different sensor mappings. Our results show participants have a preference for direct physiological control in games. This has two major design implications for physiologically controlled games: (1) Direct physiological sensors should be mapped intuitively to reflect an action in the virtual world; (2) Indirect physiological input is best used as a dramatic device in games to influence features altering the game world.