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Handheld Electronic Devices
Abstract
From PDAs to cell phones to MP3 players, handheld electronic devices are ubiquitous. Human factors engineers and designers have a need to remain informed about advances in research on user interface design for this class of devices. This review provides human factors research summaries and research-based guidelines for the design of handheld devices. The major topics include anthropometry (fitting the device to the hand), input (types of device control and methods for data entry), output (display design), interaction design (one-handed use, scrolling, menu design, image manipulation, and using the mobile Web), and data sharing (among users, devices, and networks). Thus, this review covers the key aspects of the design of handheld devices, from the design of the physical form of the device through its hardware and software, including its behavior in networks.
... Touch-typing speeds on desktop QWERTY keyboards range from 20 WPM to over 60 WPM for expert typists (MacKenzie & Soukoreff, 2002b). As a result, the standard QWERTY keyboard is considered to be the gold standard against which to assess the efficiency other input methods (Lewis, Commarford, Kennedy, & Sadowski, 2008). Physical size is a major factor for mobile devices. ...
... Although other types of input methods exist, such as chording keyboards, speech recognition, handwriting recognition, and gesture-based input, these methods are not applicable given the constraints of the devices considered in this research. For comprehensive reviews of mobile text entry methods, see MacKenzie and Soukoreff (2002b) or Lewis et al. (2008). ...
... Successive key presses are segmented using either a timeout or a dedicated kill key. Despite the problems identified for the multi-tap method, this method is still the most common text input method for mobile phones (MacKenzie & Soukoreff, 2002b;Lewis et al., 2008). ...
Despite the increase in popularity of handheld devices, text entry on such devices is becoming more difficult due to reduced form factors that limit display size, input modes, and interaction techniques. In an effort to circumvent these issues, research has found that five-key methods are effective for text entry on devices such as in-car navigation systems, television and gaming controllers, wrist watches, and other small devices. Five-key text entry methods use four directional keys to move a selector over an on-screen keyboard and an Enter key for selection. Although other researchers have described five-key character layouts using alphabetical order and predictive layouts based on digraph frequencies, there is considerable latitude in designing the rest of a comprehensive on-screen keyboard. Furthermore, it might be possible to capitalize on the relative strengths of the alphabetic and predictive layouts by combining them in a hybrid layout. Thus, this research examines the design of alternative keyboard layouts for five-key text entry techniques. Three keyboard layouts (Alphabetical, Predictive, and Hybrid) were selected to represent standard and less familiar arrangements. The analysis centered on a series of controlled experiments conducted on a research platform designed by the author. In this work, when the immediate usability of three alternative keyboard layouts for supporting five-key text entry was investigated, results indicated no statistically significant differences in performance across the tested keyboards. Furthermore, experimental results show that following immediate usability, but still at the onset of learning, there was no overall difference in performance among the three keyboard layouts across four text types. However, the Alphabetical keyboard surpassed both the Predictive and Hybrid keyboards in text entry speed in typing Web addresses. The nonstandard keyboards performed superior to the Alphabetical keyboards in typing Words/Spaces and Sentences, but performed no better in typing Address strings than the Alphabetical. Use of mixed effects modeling suggested that the longitudinal data was best fitted by a quadratic model. Text entry performance on all three layouts improved as a function of practice, demonstrating that participants could learn the unfamiliar layouts to complete text entry tasks. Overall, there was no indication that use of nonstandard layouts impedes performance. In fact, trend in time data suggests that the learning rates were greater for the nonstandard keyboards over the standard layout. Overall, participants preferred the Hybrid layout. In summary, this dissertation focused on creating and validating novel and effective five-key text entry techniques for constrained devices.
... For mobile finger-operated touchscreens, target acquisition assistance is even more relevant (cf. Lewis, Commarford, Kennedy, & Sadowski, 2008). Touching small targets with the relatively large finger while even occluding the actual target results is difficult (the "fat finger" problem). ...
Modern handheld devices can act as “magic lenses” for public displays and enable camera-based real-time interaction with their contents, thus allowing for manifold interactive applications in public space. To learn more about the characteristics of common techniques and to provide guidelines for new ones, a comparative user study was conducted. With regard to two basic task types (selection and translation) and two typical devices (smartphone and tablet), three interaction techniques in-depth were evaluated: direct touch-based input (Touch), cross-hair targeting (Target), and a new technique based on a dynamic cross-hair on the screen that snaps to visible nearby screen objects (Snap Target). The study results indicate that successful interaction with the Touch technique strongly depends on the usage context: Although Touch enables fast selection, it incurs many errors when small targets have to be selected on a smartphone. Target supports such difficult selections better, but Snap Target proved to be most robust in both investigated task types. Also, users stated that they felt best supported by the latter technique. Cross-hair-based techniques, especially Snap Target, were found to be well suitable for scenarios where several device types need to be supported under similar conditions. Implications and further work are discussed.
... We define form factor as the physical platform that comprises the mobile device. It is an indication of how well a device matches human anthropometric characteristics, such as hand dimensions, thumb and finger dexterity (Lewis et al., 2008), and how consistent the device is with user expectations and past experience. Thus, the device's form factor is a key consideration for ensuring its usability and ultimate user acceptance for mLearning and mSupport. ...
Mobile workers frequently require access to task-relevant instruction or knowledge in remote work environments where desktop or even laptop computers are impractical. Recently there has been a convergence of enabling technologies and an increased interest in the use of mobile devices to support worker learning (mLearning) and performance (mSupport). Most of this interest has been focused on mLearning rather than mSupport. However, what works for mLearning may not work for mSupport. Therefore, there is a need to better understand mLearning and mSupport, as well as the characteristics of mobile devices, their users, and their operational environments, to maximize the value of mobile devices. We provide a discussion of mLearning and mSupport that focuses on six user-centered issues likely to determine mobile device effectiveness and user acceptance, and recommend solutions: 1) device characteristics, 2) form factor, 3) user interaction styles, 4) task characteristics, 5) content management, and 6) context awareness.
... Errors and error handling are important dimensions to consider when designing and evaluating text-entry methods. Previous studies of selection-based entry (Bellman & MacKenzie, 1998; MacKenzie, 2002; Sandnes et al., 2004) have not included error correction (only measuring words per minute, sometimes with a correction for errors), but the only way to measure true text entry throughput is with correct words per minute (Lewis et al., 2008). Consequently, the tool provides a delete key to allow participants to correct input errors. ...
An emerging area of research in engineering psychology is the evaluation of text entry for mobile devices using a small number of keys for the control of cursor direction and character selection from a matrix of characters (i.e., selection-based data entry). The present article describes a software tool designed to reduce time and effort in the development of prototypes of alternative selection-based text-entry schemes and their empirical evaluation. The tool, available for distribution to researchers, educators, and students, uses Action Script code compiled into an executable file that has an embedded Adobe Flash Player and is compatible with most operating systems (including Microsoft Windows, Apple OSX, and Linux).
Interaction with a smartphone occupies a large amount of time of day. Sometimes people are using mobile phone sizes which are either too large or too small. As per the different task is concern, users may find trouble with the mobile phones having extreme sizes. Hence, perceived handiness is very important factor which may be associated with satisfaction of mobile phone use. On the other side, hand anthropometry may be another determinant of mobile size preference. Hence, this study aims to relate hand anthropometry, smartphone handiness and mobile size preference and to determine the most preferred size of the mobile phone from a range of mobile phones. It was observed that there was a significant negative correlation exists between hand anthropometric dimensions and mobile handiness or size preference scores. This result indicated that users prefer a mobile phone which is comparatively bigger in size than the size of their hands. In addition, people perceived mobile phones as less handy those are either too small in size or too big in size. Smartphone with medium size (H: 138.0 mm, W: 70.0 mm, D: 8.0 mm, V: 77280.0 mm³) was most handy and preferred by the most users, among studied mobile phones.
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.
As the full-touch screen is being implemented in more smart phones, controllability of touch icons need to be considered. Previous research focused on recommendations for absolute key size. However, the size of tactual input on touch interface is not precisely equal to the icon size. This study aims to determine the suitable touchable area to improve touch accuracy. In addition, there was an investigation into the effect of layout (3 × 4, 4 × 5, 5 × 6, and 6 × 8) and icon ratio (0.5, 0.7, and 0.9). To achieve these goals, 40 participants performed a set of serial tasks on the smart phone. Results revealed that the layout and icon ratio were statistically significant on the user response: input offset, hit rate, task completion time, and preference. The 3 × 4 and 4 × 5 layouts were shown to have better performance. The icon ratio of 0.9 was shown to have greater preference. Furthermore, the hit rate (proportion of correct input) of touchable area was estimated through the bivariate normal distribution of input offset. The hit rate could vary, depending on the size of touchable area, which is a rectangle that yields a specific hit rate. A derivation procedure of the touchable area was proposed to guarantee the desirable hit rate. Meanwhile, the locations of the central region indicated a pattern of vertical touch and showed better performance. The users felt more difficulty when approaching the edge of the frame. The results of this study could be used in the design of touch interfaces for mobile devices.
La psychologie expérimentale appliquée est une expérimentation psychologique explicitement orientée vers des préeoccupations pratiques. Ces recherches suscitent actuellement un grand intérêt. On recense dans cet article les domaines qui ont été abordés récemment par les recherches expérimentales appliquées: certains d'entre eux sont explorés depuis longtemps. Quelques observations sont faites à propos des impulsions technologiques et démographiques en faveur des travaux d'application.
Applied experimental psychology is defined as psychological experimentation explicitly addressed to practical concerns. Interest in such research appears to be high at present. Problem areas that have been addressed recently by applied experimental research, some of which have been areas of interest for a long time, are noted. Some observations are made regarding technological and demographic stimuli for applied work.
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.
By modeling users' natural spoken and multimodal communication patterns, more powerful and highly reliable interfaces can be designed that support emerging mobile technology. In this paper, we highlight three different examples of research that is advancing state-of-the-art mobile technology. The first is the development of fusion-based multimodal systems, such as ones that combine speech and pen or touch input, which are substantially improving the robustness and stability of system recognition. The second is modeling of multimodal communication patterns to establish open-microphone engagement techniques that work in challenging multi-person mobile settings. The third is new approaches to adaptive processing, which are able to transparently guide user input to match system processing capabilities. All three research directions are contributing to the design of more reliable, usable, and commercially promising mobile systems of the future.
The purpose of this study was to compare three input methods (standard keyboard, predictive keyboard, and perfect handwriting recognition) considering user input rates and preferences. Six participants used all three input methods to enter both normal text and addresses. Participants indicated that they preferred to use the standard keyboard. The average input rate for handwriting was fastest, but also much more variable than the other methods. Despite its speed, participants generally found it difficult to write comfortably and legibly on the small (35times115 mm) display. The input rate for the standard keyboard was more than twice the input rate for the predictive keyboard. These results suggest that, for small devices, neither handwriting recognition nor predictive keyboards would effectively replace the standard keyboard layout. Even with perfect handwriting recognition, users seem to prefer tapping on a small standard keyboard unless the device's hardware design allows comfortable handwriting input.
The purpose of the present study was to test and evaluate three onscreen keyboard arrangements with indirect input devices. Studies conducted for hard keyboard arrangements have considered various factors affecting typing; however, differences between the nature of the hard and on-screen keyboards tasks preclude extrapolation from hard keyboard studies to onscreen keyboard designs. In this study, Finger Placement and Non-Finger Placement typists provided data for Stimuli (Word vs. Non-Words), Devices (Mouse vs. Arrow Keys), and Keyboards (1-Row Alphabetical, 3-Row Alphabetical, and QWERTY arrangements). The primary data collection tasks were two movement tasks and a typing task. The typing task consisted of having the user type a given Stimulus utilizing one of the on-screen keyboard arrangements and input devices. The movement task served as a control for movement time in the typing task. At the conclusion of the study, users were asked to rank order their preference for keyboard arrangement and input device. The QWERTY keyboard resulted in the fastest overall input times, and was the most preferred arrangement overall. Interaction between Device and Keyboard showed that with the mouse, input times for the 1-Row Alphabetical were slower than the QWERTY; whereas, with the arrow keys, input times were equivalent. However, this change in relative performance under the 1-Row Alphabetical arrangement for the two devices can be simply attributed to movement time. After statistically removing the effects of movement time from the typing task, the 1-Row Alphabetical arrangement was equivalent to the QWERTY for both input devices. Conclusions suggest potential incompatibility between the mouse interface and the 1-Row Alphabetical arrangement used in this study.
Two experiments were conducted to determine the optimum mode of operation of the "scroll" keys on a visual display terminal. One mode involved "moving the data"; that is, pressing the "scroll up" key moved the data up, thus displaying data toward the end of the file. The other mode involved "moving the window"; pressing the "window up" key moved the window up, thus displaying data toward the beginning of the file. A total of 281 novice subjects were tested under a variety of experimental conditions. Results showed that in most cases, subjects in the window groups performed significantly faster and with significantly fewer moves than did subjects in the scroll groups. When allowed to "self-define" the system, a significant majority of the subjects defined the system to window. Explaining and demonstrating the appropriate concept had no significant effect on performance, nor did the use of key top graphic "scroll" figures.
This study investigated the effects of visual and tactile key discrimination and kinesthetic and auditory feedback on membrane keypads. More specifically, metal domes, embossed key edges and tone were examined.
Fortyeight subjects were used in a 2 × 2 × 2 factorial design with two levels of key discrimination (with and without embossed key edges), two levels of kinesthetic feedback (with and without metal domes), and two levels of auditory feedback (with and without a 1000 Hz tone). Several types of preference scales along with keying time and error rate were used as comparative measures. Results indicated that key discrimination provided by embossed key edges and feedback provided by metal domes and auditory tones had significant effect on keying performance and operator ratings of membrane keypads. Auditory feedback paired with tactile and/or kinesthetic feedback yielded the best performance and preference scores.
The primary recognition process represents a synthesis of the preperceptual representation of these speech sounds. This chapter focuses on the temporal course of the primary recognition or synthesis process. It presents a schematic representation of the primary recognition process in the framework of an information-processing model. This representation of the recognition process rests on certain assumptions about the structure and function of the human information-processing system: (1) the preperceptual auditory image holds information about the stimulus and this information remain there until primary recognition has occurred, and (2) a description of this stimulus information is available in long-term memory so that recognition can occur. The primary recognition process finds the best match between the preperceptual image and the description in long-term memory. Recognition of the stimulus involves a transformation of the information in the preperceptual auditory image, resulting in a synthesized percept of the stimulus. The stimulus for recognizing speech is a sound pattern that can be described by fluctuations in sound pressure over time.
Existing devices for communicating information to computers are bulky, slow, or unreliable. Dasher is an interface incorporating language modeling and driven by continuous two-dimensional gestures (e.g., a mouse, a stylus, or eye-tracker). Tests have shown that, after 1 hr of practice, novice users reach a writing speed of about 20 words per minute (wpm) while taking dictation. Experienced users achieve writing speeds of about 34 wpm, compared with typical 10-finger keyboard typing of 40 to 60 wpm. Although the interface is slower than a conventional keyboard, it is simple to use and could be used on personal data assistants and by motion-impaired computer users. Dasher can readily be used to enter text from any alphabet.
Two experiments examined the entry of alphabetic characters on an enhanced telephone system. Size constraints with the overall unit resulted in a small keypad which restricted users to a one or two finger typing strategy. The first experiment compared the standard Sholes arrangement of keys (QWERTY), an alphabetically organized keypad (ABC) and a numeric code method of entry (NC) which utilized the touch telephone numeric pad. Thirty naive subjects were randomly assigned to one of the three conditions. Results showed that the NC method was significantly slower than the other approaches and was rated negatively by subjects. It was concluded that such an approach is unacceptable for a consumer product like the enhanced telephone. Experiment 2 further examined performance and preference for QWERTY versus ABC arrangements. Twenty subjects completed standardized text entry tasks on both arrangements with order counterbalanced. Performance was clearly faster on the QWERTY keypad and subjects recorded an overwhelming preference for it over the ABC arrangement, regardless of their previous keyboard experience. These results extend the superiority of QWERTY over ABC to small keypads and a restricted typing strategy.