Poika Isokoski

Device independent text input: a rationale and an example

Individual characters and text are the main inputs in many computing devices. Currently there is a growing trend in developing small portable devices like mobile phones, personal digital assistants, GPS-navigators, and two-way pagers. Unfortunately these portable computing devices have different user interfaces and therefore the task of text input takes many forms. The user, who in the future is likely to have several of these devices, has to learn several text input methods. We argue that there is a need for a universal text input method. A method like this would work on a wide range of interface technologies and allow the user to transfer his or her writing skill without device-specific training. To show that device independent text input is possible, we present a candidate for a device independent text entry method that supports skill transfer between different devices. A limited longitudinal study was conducted to achieve a proof of concept evaluation of our Minimal Device Independent Text Input Method (MDITIM). We found MDITIM writing skill acquired with a touchpad to work almost equally well on mouse, trackball, joystick and keyboard without any additional training. Our test group reached on average 41% of their handwriting speed by the end of the tenth 30-minute training session.

Gaze controlled games

The quality and availability of eye tracking equipment has been increasing while costs have been decreasing. These trends increase the possibility of using eye trackers for entertainment purposes. Games that can be controlled solely through movement of the eyes would be accessible to persons with decreased limb mobility or control. On the other hand, use of eye tracking can change the gaming experience for all players, by offering richer input and enabling attention-aware games. Eye tracking is not currently widely supported in gaming, and games specifically developed for use with an eye tracker are rare. This paper reviews past work on eye tracker gaming and charts future development possibilities in different sub-domains within. It argues that based on the user input requirements and gaming contexts, conventional computer games can be classified into groups that offer fundamentally different opportunities for eye tracker input. In addition to the inherent design issues, there are challenges and varying levels of support for eye tracker use in the technical implementations of the games.

Model for unistroke writing time

Unistrokes are a viable form of text input in pen-based user interfaces. However, they are a very heterogeneous group of gestures the only common feature being that all are drawn with a single stroke. Several unistroke alphabets have been proposed including the original Unistrokes, Graffiti, Allegro, T-Cube and MDITIM. Comparing these methods usually requires a lengthy study with many writers and even then the results are biased by the earlier handwriting experience that the writers have. Therefore, a simple descriptive model for predicting the writing time for an expert user on any given unistroke alphabet thus enabling sounder argumentation on the properties of different writing methods.

Now Dasher! Dash away!: longitudinal study of fast text entry by Eye Gaze

Dasher is one of the best known inventions in the area of text entry in recent years. It can be used with many input devices, but studies on user performance with it are still scarce. We ran a longitudinal study where 12 participants transcribed Finnish text with Dasher in ten 15-minute sessions using a Tobii 1750 eye tracker as a pointing device. The mean text entry rate was 2.5 wpm during the first session and 17.3 wpm during the tenth session. Our results show that very high text entry rates can be achieved with eye-operated Dasher, but only after several hours of training.

Performance of menu-augmented soft keyboards

We report results on the performance of the combination of soft keyboards and marking menus. A model of expert user performance indicated an 11 - 37% (depending on the keyboard layout) improvement in text entry rate over the same keyboard without the menu. To verify the advantage in real usage, we conducted two experiments using the QWERTY keyboard layout with and without the menu. The first experiment imitated nearly perfect cognitive performance and measured motor performance. Using the menu saved time. The second experiment measured performance in a realistic text entry task. Initially using the menu slows down text entry. By the end of the 20-session experiment both conditions were equally fast. With continued practice text entry is likely to be faster with the menu.

SplitBoard: A Simple Split Soft Keyboard for Wristwatch-sized Touch Screens

Text entry on a smartwatch is a challenging problem due to the devices limited screen area. In this paper, we introduce the SplitBoard, which is a soft keyboard designed for a smartwatch. As the user flicks left or right on the keyboard, it switches between the left and right halves of a QWERTY keyboard. We report the results of two user experiments where the SplitBoard was compared to an ordinary QWERTY keyboard, the ZoomBoard, SlideBoard, and Qwerty-like keypad. We measured the initial performance with new users for each method. The SplitBoard outperformed all other techniques in the experiments. The SplitBoard is expected to be a viable option for smartwatch text entry because of its light processing requirements, good performance, and immediate learnability.

Quikwriting as a multi-device text entry method

Quikwriting is a previously published technique for entering text into computers using a stylus. We report results of a longitudinal study on user performance with it. In addition to the original stylus-based usage mode we designed modes for joystick and keyboard thus making Quikwriting compatible with a wide range of computing devices. Twelve participants used the stylus and joystick modes in 20 sessions for a total of ten hours. By the end of the experiment their text entry rate was 16 wpm in the stylus mode and 13 wpm in the joystick mode. At the end we conducted a test to verify that Quikwriting skill transfers to the keyboard mode. Text entry rate for the first five minutes of use in the keyboard mode was 6 wpm. In summary, the stylus mode was not particularly fast, but we found Quikwriting suitable for multi-device use.

Gaze gestures and haptic feedback in mobile devices

Anticipating the emergence of gaze tracking capable mobile devices, we are investigating the use of gaze as an input modality in handheld mobile devices. We conducted a study of combining gaze gestures with vibrotactile feedback. Gaze gestures were used as an input method in a mobile device and vibrotactile feedback as a new alternative way to give confirmation of interaction events. Our results show that vibrotactile feedback significantly improved the use of gaze gestures. The tasks were completed faster and rated easier and more comfortable when vibrotactile feedback was provided.

Comparison of two touchpad-based methods for numeric entry

Small hand-held touchpads can be used to replace stylus-based digitizing tablets when the use of a stylus is not convenient. In text entry tasks where the writing surface is held in a hand the error rate becomes a problem. The small size of strokes compared to the width of the fingertip and the additional imprecision caused by the interaction of the pad and finger movements make input very imprecise. We describe a new improved clock-face based stroke system for entering numbers with a touchpad. In a 20-session user study with 6 users we found slightly better throughput of successfully entered numbers with the proposed new system. This advantage was mainly due to lower error rate with the new system. User preference similarly slightly favored the new system over an earlier straightforward proposal based on the clock metaphor

Gestures and widgets: performance in text editing on multi-touch capable mobile devices

We describe the design and evaluation of a gestural text editing technique for touchscreen devices. The gestures are drawn on top of the soft keyboard and interpreted as commands for moving the caret, performing selections, and controlling the clipboard. Our implementation is an Android service that can be used in any text editing task on Android-based devices. We conducted an experiment to compare the gestural editing technique against the widget-based technique available on a smartphone (Samsung Galaxy II with Android 2.3.5). The results show a performance benefit of 13-24% for the gestural technique depending on the font size. Subjective feedback from the participants was also positive. Because the two editing techniques use different input areas, they can co-exist on a device. This means that the gestural editing can be added on any soft keyboard without interfering with user experience for those users that choose not to use it.