In view of the difficulties in evaluating computer pointing devices across different tasks within dynamic and complex systems, new performance measures are needed. This paper proposes seven new accuracy measures to elicit (sometimes subtle) differences among devices in precision pointing tasks. The measures are target re-entry, task axis crossing, movement direction change, orthogonal direction change, movement variability, movement error, and movement offset. Unlike movement time, error rate, and throughput, which are based on a single measurement per trial, the new measures capture aspects of movement behaviour during a trial. The theoretical basis and computational techniques for the measures are described, with examples given. An evaluation with four pointing devices was conducted to validate the measures. A causal relationship to pointing device efficiency (viz. throughput) was found, as was an ability to discriminate among devices in situations where differences did not otherwise appear. Implications for pointing device research are discussed.

Meeting the increasing demand for desktop-like applications on mobile products requires powerful interaction techniques. One candidate is GUI-style point-andclick interaction using an integrated pointing device that supports handheld use. We tested an isometric joystick for this purpose. Two prototypes were built. They were designed for thumb operation and included a separate selection button. Twelve participants performed point-and-select tasks. We tested both one-handed and two-handed interaction, and selection using the separate selection button and the joystick's integrated press-toselect feature. A notebook configuration served as a reference. Results for the handheld conditions, both one-handed and two-handed, were just slightly off those for the notebook condition, suggesting that an isometric joystick is suitable as a pointing device for handheld terminals. Inadvertent selection while moving the pointer yielded high error rates for all conditions using press-to-select. A separate select button is therefore needed to ensure accurate selection. Key words: Isometric joystick, pointing devices, handheld devices, ISO 9241, Fitts' law. 1

A gestural text entry method for mobile is presented. Unlike most mobile phone text entry methods, which rely on repeatedly pressing buttons, our gestural method uses an isometric joystick and the EdgeWrite alphabet to allow users to write by making letter-like “pressure strokes. ” In a 15-session study comparing character-level EdgeWrite to Multitap, subjects ’ speeds were statistically indistinguishable, reaching about 10 WPM. In a second 15-session study comparing word-level EdgeWrite to T9, the same subjects were again statistically indistinguishable, reaching about 16 WPM. Uncorrected errors were low, around 1 % or less for each method. In addition, subjective results favored Edge-Write. Overall, results indicate that our isometric joystickbased method is highly competitive with two commercial keypad-based methods, opening the way for keypad-less designs and text entry on tiny devices. Additional results showed that a joystick on the back could be used at about 70 % of the speed of the front, and the front joystick could be used eyes-free at about 80 % of the speed of normal use.

A joystick text entry method for game controllers and mobile phones would be valuable, since these devices often have joysticks but no conventional keyboards. But prevalent joystick text entry methods are slow because they are selection-based. EdgeWrite, a new joystick text entry method, is not based on selection but on gestures from a unistroke alphabet. Our experiment shows that this new method is faster, leaves fewer errors, and is more satisfying than date stamp and selection keyboard (two prevalent selection-based methods) for novices after minimal practice. For more practiced users, our results show that EdgeWrite is at least 1.5 times faster than selection keyboard, and 2.4 times faster than date stamp.

We present a novel method of dynamic C-D gain adaptation that improves target acquisition for users with motor impairments. Our method, called the Angle Mouse, adjusts the mouse C-D gain based on the deviation of angles sampled during movement. When angular deviation is low, the gain is kept high. When angular deviation is high, the gain is dropped, making the target bigger in motor-space. A key feature of the Angle Mouse is that, unlike most pointing facilitation techniques, it is target-agnostic, requiring no knowledge of target locations or dimensions. This means that the problem of distractor targets is avoided because adaptation is based solely on the user’s behavior. In a study of 16 people, 8 of which had motor impairments, we found that the Angle Mouse improved motor-impaired pointing throughput by 10.3 % over the Windows default mouse and 11.0 % over sticky icons. For able-bodied users, there was no significant difference among the three techniques, as Angle Mouse throughput was within 1.2 % of the default. Thus, the Angle Mouse improved pointing performance for users with motor impairments while remaining unobtrusive for able-bodied users. Author Keywords: Mouse pointing, pointing facilitation, pointing techniques, control-display gain, dynamic gain adjustment, target acquisition, cursor control. ACM Classification Keywords: H.5.2. [Information interfaces and presentation]: User interfaces—input devices and strategies. K.4.2. [Computers and society]: Social issues—assistive technologies for persons with disabilities.

The increasing quantity and complexity of in-vehicle systems creates a demand for user interfaces which are suited to driving. The steering wheel is a common location for the placement of buttons to control navigation, entertainment, and environmental systems, but what about a small touchpad? To investigate this question, we embedded a Synaptics StampPad in a computer game steering wheel and evaluated seven methods for selecting from a list of over 3000 street names. Selection speed was measured while stationary and while driving a simulator. Results show that the EdgeWrite gestural text entry method is about 20 % to 50 % faster than selection-based text entry or direct list-selection methods. They also show that methods with slower selection speeds generally resulted in faster driving speeds. However, with EdgeWrite, participants were able to maintain their speed and avoid incidents while selecting and driving at the same time. Although an obvious choice for constrained input, on-screen keyboards generally performed quite poorly. CR Categories: H.5.2. Information interfaces and presentation: User interfaces — Input devices and strategies.

In most graphical user interfaces, a substantial part of the user's interaction involves targeting screen objects with the mouse cursor. Targeting tasks with small targets are visually demanding, and can cause users difficulty in some circumstances. These circumstances can arise either if the user has a visual disability or if factors such as fatigue or glare diminish visual acuity. One way of reducing the sensory demands of targeting is to add redundant feedback to the interface that indicates when the user has successfully acquired a target. Under optimal viewing conditions, such feedback has not significantly improved targeting performance. However, we hypothesized that targeting feedback would be more beneficial in a visually stressed situation. We carried out an experiment in which normally sighted participants in a reduced-acuity environment carried out targeting tasks with a mouse. We found that people were able to select targets significantly faster when they were given targeting feedback, and that they made significantly fewer errors. People also greatly preferred interfaces with feedback to those with none. The results suggest that redundant targeting feedback can improve the usability of graphical interfaces, both for low-vision users and also for normally sighted users in visually stressed environments. 1.

Prior research shows that people with motor impairments face considerable challenges when using conventional mice and trackballs. One challenge is positioning the mouse cursor within confined target areas; another is executing a precise click without slipping. These problems can make mouse pointing in graphical user interfaces very difficult for some people. This article explores goal crossing as an alternative strategy for more accessible target acquisition. In goal crossing, targets are boundaries that are simply crossed by the mouse cursor. Thus, goal crossing avoids the two aforementioned problems. To date, however, researchers have not examined the feasibility of goal crossing for people with motor difficulties. We therefore present a study comparing area pointing and goal crossing. Our performance results indicate that although Fitts ’ throughput for ablebodied users is higher for area pointing than for goal crossing (4.72 vs. 3.61 bits/s), the opposite is true for users with motor impairments (2.34 vs. 2.88 bits/s). However, error rates are higher for goal crossing than for area pointing under a strict definition of crossing errors (6.23 % vs. 1.94%). We also present path analyses and an examination of submovement velocity, acceleration, and jerk (the change in acceleration over time). These results show marked differences between crossing and pointing and almost categorically favor crossing. An important finding is that crossing reduces jerk for both participant groups, indicating more fluid, stable motion. To help realize the potential of goal crossing for computer access, we offer design concepts for crossing widgets that address the occlusion problem, which occurs when one crossing goal obscures another in persistent mousecursor interfaces. This work provides the motivation and initial steps for further exploration of goal crossing on the desktop, and may help researchers and designers to radically reshape user interfaces to provide accessible goal crossing, thereby lowering barriers to access.

NEC Foundation of America, NISH, Synaptics, and A.T. Sciences.

Isometric and elastic devices are most compatible with a rate control mapping. However, the effect of elastic stiffness has not been thoroughly investigated nor its interaction with control gain. In a controlled experiment, these factors are investigated along with user feedback regarding ease-of-use and fatigue. The results reveal a U-shaped profile of control gain vs. movement time, with different profiles for different stiffness levels. Using the optimum control gain for each stiffness level, performance across stiffness levels was similar. However, users preferred lower stiffness and lower control gain levels due to increased controller displacement. Based on these results, design guidelines for elastic rate control devices are given.