論文アブストラクト： Text selection on touch devices can be a difficult task for users. Letters and words are often too small to select directly, and the enhanced interaction techniques provided by the OS -- magnifiers, selection handles, and methods for selecting at the character, word, or sentence level -- often lead to as many usability problems as they solve. The introduction of force-sensitive touchscreens has added another enhancement to text selection (using force for different selection modes); however, these modes are difficult to discover and many users continue to struggle with accurate selection. In this paper we report on an investigation of the design of touch-based and force-based text selection mechanisms, and describe two novel text-selection techniques that provide improved discoverability, enhanced visual feedback, and a higher performance ceiling for experienced users. Two evaluations show that one design successfully combined support for novices and experts, was never worse than the standard iOS technique, and was preferred by participants.
論文アブストラクト： We present ForceBoard, a pressure-based input technique that enables text entry by subtle finger motion. To enter text, users apply pressure to control a multi-letter-wide sliding cursor on a one-dimensional keyboard with alphabetical ordering, and confirm the selection with a quick release. We examined the error model of pressure control for successive and error-tolerant input, which was incorporated into a Bayesian algorithm to infer user input. A user study showed that, after a 10-minute training, the average text entry rate reached 4.2 wpm (Words Per Minute) for character-level input, and 11.0 wpm for word-level input. Users reported that ForceBoard was easy to learn and interesting to use. These results demonstrated the feasibility of applying pressure as the main channel for text entry. We conclude by discussing the limitation, as well as the potential of ForceBoard to support interaction with constraints from form factor, social concern and physical environments.
論文アブストラクト： The activation point of a button is defined as the depth at which it invokes a make signal. Regular buttons are activated during the downward stroke, which occurs within the first 20 ms of a press. The remaining portion, which can be as long as 80 ms, has not been examined for button activation for reason of mechanical limitations. The paper presents a technique and empirical evidence for an activation technique called Impact Activation, where the button is activated at its maximal impact point. We argue that this technique is advantageous particularly in rapid, repetitive button pressing, which is common in gaming and music applications. We report on a study of rapid button pressing, wherein users' timing accuracy improved significantly with use of Impact Activation. The technique can be implemented for modern push-buttons and capacitive sensors that generate a continuous signal.
論文アブストラクト： Picking values from long ordered lists, such as when setting a date or time, is a common task on smartphones. However, the system pickers and tables used for this require significant screen space for spinning and dragging, covering other information or pushing it off-screen. The Force Picker reduces this footprint by letting users increase and decrease values over a wide range using force touch for rate-based control. However, changing input direction this way is difficult. We propose three techniques to address this. With our best candidate, Thumb-Roll, the Force Picker lets untrained users achieve similar accuracy as a standard picker, albeit less quickly. Shrinking it to a single table row, 20% of the iOS picker height, slightly affects completion time, but not accuracy. Intriguingly, after 70 minutes of training, users were significantly faster with this minimized Thumb-Roll Picker compared to the standard picker, at the same accuracy and only 6% of the gesture footprint. We close with application examples.