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Chapter 54. Keys and Keyboards
Abstract
Keyboards are in widespread use both on typewriters and as input devices to computers. Early refinements of the typewriter keyboard aimed at improving its mechanical action so that it would operate more smoothly with fewer malfunctions. Later, the work focused on improving typing speed and accuracy. This chapter describes keyboard design factors that affect skilled typing and data entry. The information presented should apply equally well to typewriter and computer keyboards. Some data also apply to telephones and other specialized keypads used for data entry tasks. Proponents of the best-publicized alternatives to the standard keyboard have generally failed to provide convincing empirical cases for their wholesale replacement of the standard, although they might see reasonable application in certain special settings. A well-designed standard keyboard is an extremely effective data-entry device and will probably remain a key component in human-computer interaction for the foreseeable future.
... This paper contributes to study of buttons as input devices [1,14,23,25,33,36,41,42,46,51,53,58,71]. A button is a transducer that registers motion of a finger, changes the state of a machine, and returns to resting state. ...
... We simulated presses with four common button types (linear, tactile, touch, mid-air). We report simulation results for (1) displacement-velocity patterns, (2) temporal precision and success rate in button activation, and (3) use of force, comparing with effects reported in empirical studies [7,36,42,46,48,53,54,59,66,69]. Over the simulations, we find evidence for the plausibility of the optimality assumption. ...
... Physical buttons are electromechanical devices that make or break a signal when pushed, then return to initial (or repushable) state when released. Physical dimensions (width, slant, and key depth), materials (e.g., plastics), and systemlevel feedback (modalities and latencies of feedback) are wellknown design parameters [46]. The travel distance at which the button is activated is called its activation point (see [67]). ...
To press a button, a finger must push down and pull up with the right force and timing. How the motor system succeeds in button-pressing, in spite of neural noise and lacking direct access to the mechanism of the button, is poorly understood. This paper investigates a unifying account based on neurome-chanics. Mechanics is used to model muscles controlling the finger that contacts the button. Neurocognitive principles are used to model how the motor system learns appropriate muscle activations over repeated strokes though relying on degraded sensory feedback. Neuromechanical simulations yield a rich set of predictions for kinematics, dynamics, and user performance and may aid in understanding and improving input devices. We present a computational implementation and evaluate predictions for common button types.
In a perfect world, it would always be possible to operate technology effortlessly and to reach the desired goal. However, in the real world many factors may make technologies difficult to use or even hinder people from using technical artefacts. Most of these factors pertain to usability (i.e., technology’s ability to fit users’ capabilities) and thus concern technological solutions from the point of view of human beings as users of technology. Therefore, designing technical artefacts that are easy to use requires understanding the psychological and mental preconditions for using technology.
A significant milestone in the development of physicallydynamic surfaces is the ability for buttons to protrude outwards from any location on a touch-screen. As a first step toward developing interaction requirements for this technology we conducted a survey of 1515 electronic push buttons in everyday home environments. We report a characterisation that describes the features of the data set and discusses important button properties that we expect will inform the design of future physically-dynamic devices and surfaces.
Keyboard optimization is concerned with the design of keyboards for different terminals, languages, user groups, and tasks. Previous work in HCI has used random search based methods, such as simulated annealing. These "black box" approaches are convenient, because good solutions are found quickly and no assumption must be made about the objective function. This paper contributes by developing integer programming (IP) as a complementary approach. To this end, we present IP formulations for the letter assignment problem and solve them by branch-and-bound. Although computationally expensive, we show that IP offers two strong benefits. First, its structured non-random search approach improves the outcomes. Second, it guarantees bounds, which increases the designer's confidence over the quality of results. We report improvements to three keyboard optimization cases.
Artificial Intelligence (AI) is the field of computer and system science concerned with intelligent machines and systems which are created by embedding intelligence to computers. Actually, no unique, or globally accepted, definition of AI exists, and the AI concept has brought a wide repertory of discussions, arguments and disagreements. This Chapter provides background material on AI that will enable the reader to appreciate the need for intelligent machines and robots ethics. Specifically, the chapter discusses the difference between human and artificial intelligence, outlines the Turing test that a machine has to pass in order to be characterized as intelligent, and provides a quick tour to applied AI.
The QWERTY type keyboard is a classical device that has been used for computers for a long time. The keyboard design of mobile devices like smartphones is an important issue to consider because of the limited space on the touch screen. This paper presents a design for symbol allocation on the QWERTY type soft keyboard. A 27-cell model, including the full stop (.), is proposed in this paper. A QWERTY type keyboard for smartphones is mainly known for its spatial compatibility, whereas the characters of the ANSI keyboard are allocated to the shoulder positions for functional auxiliary input methods such as the long pressing method.
This study compares the use of a conventional keyboard (CK) and a prototype ultra-low profile MultiTouch keyless keyboard (MTK) that only requires contact force to register a keystroke and allows mousing and gestural input on the same surface. Twelve subjects completed eight randomly assigned 7.5-minute typing tasks of text passages of similar difficulty and identical length for each keyboard condition. Typing speed, accuracy, wrist postures and user comfort were measured. Subjects, typed slower (F1, 11 = 41.86, p=0.000) and less accurately (F1,11 = 23.55, p=0.001) on the MTK during the typing tasks. Mean wrist extension was lower for the MTK (F1,11= 10.205, p=0.000) while radial and ulnar deviation did not differ significantly between the two keyboards. Subjects preferred the CK and reported a higher level of ease (F1,11 = 49.732, p=0.00) and enjoyment (F1,11 = 51.129, p=0.00) during its use. In terms of comfort, subjects reported a higher level of ease and enjoyment in the CK condition. Familiarity and fatigue effects affected the results.
Remote controls are especially problematic for writing text, something necessary in many interactive digital TV applications (IDTV). In the context of research aimed at finding effective entry methods for IDTV applications, an empirical investigation was carried out and is presented in this article. The study analyzed the errors committed by 82 users in an experiment in which they wrote 7,395 sentences. Several typing methods suitable for IDTV contexts were used for experimentation. There were 3,562 of the sentences that registered at least one error. These errors were classified and their main causes analyzed, the particular characteristics of the users taken into account. The results show that the most frequent errors are proximity mistakes in all the evaluated methods. They appear in between 13.75% and 32.31% of the sentences, depending on the input method. Also, age and background are major aspects affecting the number and type of mistakes. The results could be the basis of changes in the design of conventional remote controls or in the design of advanced techniques for error recognition and correction.
Custom closets customers usually lack the expertise to design their desired closet. The use of a software tool that incorporates the design expertise might allow them to sketch their ideas without third party oversight. While architecture related applications are very powerful and make it possible to have an accurate graphical representation of real world, these Computer-Aided Design (CAD) tools demand high technical training and their use in the engineering field is generic. Our work, framed within the development of a rapid prototyping tool of custom closets called Sketch Arm, introduces an interaction proposal that seeks to minimize the time and complexity associated with typical operations in CAD. Supported by multi-touch capabilities of today’s mobile devices, our system allows users to manipulate the closet structure directly in real time by using a minimalist graphical user interface (GUI) together with a touch interface based on easily recognizable gesture patterns. Direct on-screen data manipulation is very attractive to the end-user in general and highly beneficial for novice IT users in particular while gesture-based interaction is extremely intuitive for performing artistic tasks. Throughout the article, we will describe in depth the designed interaction system and we will present the original solutions we made to common problems in touch systems like accuracy and occlusion.
The time and labor demanded by a typical laboratory-based keyboard evaluation are limiting resources for algorithmic adjustment and optimization. We propose Remulation, a complementary method for evaluating touchscreen keyboard correction and recognition algorithms. It replicates prior user study data through real-time, on-device simulation. We have developed Octopus, a Remulation-based evaluation tool that enables keyboard developers to efficiently measure and inspect the impact of algorithmic changes without conducting resource-intensive user studies. It can also be used to evaluate third-party keyboards in a "black box" fashion, without access to their algorithms or source code. Octopus can evaluate both touch keyboards and word-gesture keyboards. Two empirical examples show that Remulation can efficiently and effectively measure many aspects of touch screen keyboards at both macro and micro levels. Additionally, we contribute two new metrics to measure keyboard accuracy at the word level: the Ratio of Error Reduction (RER) and the Word Score.
This paper shows that the chord principle, used to couple chords
one-to-one with phonemes, can be applied to the design of a new and
powerful keyboard for the stenograph. The new keyboard is called the
minimum chord stenograph (MCS). The training time is quite short. Within
the limits imposed by no more than 50 hours' training, MCS' input data
rates are superior to those from the old stenograph. One can definitely
state that MCS requires a modest time to learn the code and, in return,
gives a means for rapid entry of phoneme-based speech. A review is given
of relevant features of the standard typewriter (QWERTY), chord
keyboards, and the normal stenograph. Detailed insight into the
operator-and-machine as a unit is provided by interval measurements t
<sub>p</sub>(r) taken directly from tests when MCS is being operated. t
<sub>p</sub>(r) is the time measured from the end of one chord and the
end of the next chord r. A pseudochannel capacity C<sub>p</sub>(r) is
used to show that MCS' performance gets better as training time is
increased. Although QWERTY works with alphabet letters as input and MCS
works with phonemes as input an attempt is made to compare QWERTY and
MCS in terms of “words per minute”. The two methods are not
very different in time to acquire a first competence, but MCS's top
speed after 50 hours of training is a little better than QWERTY's speed
for operators all of whom had at least a year of training and
usage