Enhanced auditory feedback for Korean touch screen keyboards

With the increasing popularity of touch screen mobile devices, improving the usability and the user experience while inputting text on these devices is becoming increasingly important. Most conventional touch screen keyboards on mobile devices rely heavily on visual feedback, while auditory feedback seldom includes any useful information about what is being inputted by the user. The auditory feedback usually simply replicates the sounds produced by a physical keyboard. This paper describes the development of an enhanced auditory feedback mechanism for a Korean touch screen keyboard called the enhanced auditory feedback (EAF) mechanism. EAF has subtle phonetic auditory feedback generated using the acoustic phonetic features of human speech. While typing with EAF, users can acquire non-invasive auditory clues about the keys pressed. In this work, we compare conventional auditory feedback for a touch screen keyboard used in touch screen mobile devices with that of EAF and explore the possibility of using enhanced auditory feedback for touch screen keyboards.     

μcaptcha: Human Interaction Proofs Tailored to Touch-Capable Devices via Math Handwriting

Online services are often protected with captchas that typically must be solved by typing on a keyboard. Now that smartphones and tablets are increasingly being used to browse the web, new captchas best suited to touch-capable devices should be devised, because entering text on soft keyboards is usually uncomfortable and error-prone. This article contributes to solving this issue with μcaptcha, a novel captcha scheme to tell humans and computers apart by means of math handwriting input. Instead of entering text with a keyboard, the user retypes a mathematical expression on a touch screen using, for example, the finger, a stylus, or an e-pen. Further, as a by-product of solving μcaptcha challenges, a valuable labeled data set of online handwritten math expressions is collected. Studies reveal that μcaptcha is accurate, fast, and easy to perform and that users find it to be both useful and enjoyable. Ultimately, this work informs an understanding of designing better web security measures.     

Efficient model of Korean graphemes based on a smartphone keyboard

Smartphones are becoming more advanced, and the use of touch input is increasing. Therefore, various keyboards can be implemented in smartphones. Unlike the button input method, the touch input method can have non-fixed keys that can be freely arranged. Many users are thus interested in the touch input method. In this paper, we propose a Korean grapheme model called ‘Auto Toggle’ by using auto switching between consonants and vowels of Hangul. Also, Auto Toggle is designed and implemented based on the Android platform. Finally, we describe the results of a performance evaluation for the number of buttons pushed for each single syllable of Hangul compared with conventional methods. Additionally, Auto Toggle results in a rapid improvement on typing speed with respect to sentence generation.     

Effect of key size and activation area on the performance of a regional error correction method in a touch-screen QWERTY keyboard

Manual text entry, which is one of the main features of mobile communications devices, decreases the competitive advantages of full touch-screen interfaces over physical interfaces. Especially for small full QWERTY keyboards, text entry becomes more problematic because of the small size of the virtual keys, absence of tactile feedback, and occlusion of virtual keys by fingers. One solution to this problem is the regional error correction, which is a predictive text entry method that activates the key corresponding to the actual activation point and also other keys within an activation area. This study investigates how the size of keys and of the activation area affect the accuracy of the regional error correction and compares the regional error correction method with the conventional finger touch method, for a touch-screen QWERTY keyboard. The regional error correction reduced both the time and the number of touches required to complete text entry when keys were small, but no difference was observed when keys were large. Users’ subjective assessments of ease of use and preference indicated greater satisfaction with the regional error correction method than without it, regardless of key size.Relevance to industry: The result of this study can be used to speed and simplify text entry in mobile devices with full-QWERTY virtual keyboards.     

Exploring touch feedback display of virtual keyboards for reduced eye movements

When typing on smartphones or palm tablets, users generally make an effort to type correctly while simultaneously checking the small keyboard and the text display. Unlike physical keyboards that allow users to perform typing based on long-term muscle memory, virtual keyboards typically require more frequent eye movements between the keyboard and the text display areas.This study proposes a new way of designing a virtual keyboard display to reduce the effort associated with frequent eye-movements. For this study, we developed virtual keyboard display systems featuring both static and dynamic word-by-word (WBW) feedback displays. The two display systems were examined in comparison with a more conventional method known as character-by-character (CBC) feedback display. We investigated user satisfaction, typing performance and the user’s eye gaze shifts. Eye gaze shifts were measured between the keyboard and the text display areas across the three conditions using self-report, log, and eye-tracking measures. In the static WBW condition, the words being typed displayed in a fixed area at the top of the virtual keyboard; in the dynamic WBW display, the words displayed in a small popup window at the tip of the selected key.Using a repeated measure experiment for the three display conditions, participants were asked to type fifteen phrases using a palm tablet while wearing eye-tracking glasses for each condition. We conducted a mixed-model design ANOVA with group (SLOW vs. FAST typing; men vs. women) as between-subject factors and display condition (CBC vs. WBW). We found a significant (11%) improvement in typing speed with the dynamic WBW over the CBC display for less experienced keyboard users. In addition, participants reported higher satisfaction with the two WBW conditions than the CBC condition. Eye fixations, dwell times, and heat map data also supported that WBW displays are advantageous for less experienced, slower typists by helping them stay focused more on the keyboard, thus reducing eye transitions to the text display. Our study systematically demonstrates how and to what extent the virtual keyboard display strategy influences typing performance and subjective experience based on self-reports and eye-tracking measures. The approach and findings of this study should provide useful information and practical guidance to mobile application developers and designers who are interested in improving virtual keyboard functionalities and user satisfaction.     

Building and testing optimized keyboards for specific text entry

OBJECTIVE: We explore how to optimally design systems for information input. BACKGROUND: As computers are introduced into ever more devices with new methods of inputting information, there is a need for specialized systems that are optimally designed for their particular use. METHOD: The study demonstrates how to use a model of text entry times to build optimized keyboards for specific sets of text. The technique is demonstrated by using Fitts' law to model text entry times. Alphabet letters are assigned to keys in a way that minimizes predicted entry time for the specified set of text. The predicted entry times are validated by an experiment in which two keyboards are optimized for different sets of text. RESULTS: Text entry is faster for the keyboard optimized for that text compared with the keyboard optimized for the other text. Learning to use the keyboards is fairly quick, with significant learning being observed after only one half-hour session. CONCLUSION: There is a need and an ability to design specialized keyboards for some situations. The study demonstrates that optimization of keyboards can decrease text entry times. APPLICATION: This research shows how to design optimized keyboards for many different situations. The approach should be useful for aviation, medical, industrial, and other specialized situations in which normal keyboard designs cannot be used.     

A powerful pseudo-syllabic text entry paradigm

This paper describes a powerful pseudo-syllabic paradigm for improving the efficiency of typing in languages with transparent orthography (i.e., languages with highly regular correspondence of orthography and phonetics). By adopting a novel orthogonal framework, keyboards are defined as two-dimensional regular arrays of keys. Non-expert users can fast and intuitively input any possible combination of pseudo-syllables, which are text entry units with simpler consonant–vowel phonemic structure. Moreover, it is possible to input single characters in the typical letter-by-letter way. For transparent languages such as Italian and Spanish, the performed tests have shown a significant improvement in the efficiency of typing texts.     

Visual and manual loadings with QWERTY-like ambiguous keyboards: Relevance of letter-key assignments on mobile phones

Mobile phone touchscreens have many ergonomic problems related to text entry. Previous studies, which attempted to use ambiguous keyboards to resolve problem of small keys, focused on the disambiguation process without consideration of the user loading on graphic user interface. This study investigates user loadings, which interfere with performance in the key selection phase when using an ambiguous keyboard. Hence, three QWERTY-like ambiguous keyboards and a standard QWERTY keyboard were compared via visual search and manual operation experiments. The visual search experiment shows that layouts with many letters per key were strongly related to long visual search times, and layouts with large keys were operated faster and more accurately in the manual operation experiment. Consequently, the trade-off between visual and manual loading differed among different letter-key assignments. This study is important in that it elucidates the impacts of visual and manual loadings on ambiguous keyboards, as well as in providing user interface designers with an enhanced understanding of how to design ambiguous keyboards based on user criteria.Relevance to industryAmbiguous keyboard designs in previous studies were generally far from the actual needs of users. This study examines the factors affecting text entry performance of users via the user-centered approach, improving the understanding of designers.     

Optimization of Split Keyboard Design for Touchscreen Devices

While many large touchscreen devices have a split keyboard option to enable two-thumb typing, there are significant differences in the design which affect users’ text entry rate. A mixed-integer programming model is developed to optimize key-to-thumb assignment with the objective of minimizing the expected time to type a character. Computer simulations are conducted to determine the optimal key dimension under different values of the Fitts’ law’s slope coefficient, typing error rate, and alternate-hand advantage phenomenon. The results show that text entry rate and the optimal key-to-thumb assignment depend on key dimensions, user’s speed-accuracy profile, and the level of alternate-hand advantage. The optimal keyboard is proposed. To validate the analytical findings, an empirical study is conducted with eighteen users and six different keyboards in terms of key dimensions and typing zone. Empirical results report between 7% and 18% improvement in the text entry rate over the other split keyboards tested.     

What input errors do you experience? Typing and pointing errors of mobile Web users

Small devices such as personal digital assistants (PDAs) are widely used to access the World Wide Web (Web). However, accessing the Web from small devices is affected by poor interface bandwidth, such as small keyboards and limited pointing devices. There is little empirical work investigating the input difficulties caused by such insufficient facilities, however, anecdotal evidence suggests that there is a link between able-bodied users of the mobile Web and motor impaired users of the Web on desktop computers. This being the case we could transfer the solutions which already exists for motor impaired users into the mobile Web and vice versa. This paper presents a user study that investigates the input errors of mobile Web users in both typing and pointing. The study identifies six types of typing errors and three types of pointing errors shared between our two user domains. We find that mobile Web users often confuse the different characters located on the same key, press keys that are adjacent to the target key, and miss certain key presses. When using a stylus, they also click in the wrong places, slide the stylus during multiple clicks, and make errors when dragging. Our results confirm that despite using different input devices, mobile Web users share common problems with motor impaired desktop users; and we therefore surmise that it will be beneficial to transfer available solutions between these user domains in order to address their common problems.     

Reactions,accuracy and response complexity of numerical typing on touch screens

Touch screens are popular nowadays as seen on public kiosks, industrial control panels and personal mobile devices. Numerical typing is one frequent task performed on touch screens, but this task on touch screen is subject to human errors and slow responses. This study aims to find innate differences of touch screens from standard physical keypads in the context of numerical typing by eliminating confounding issues. Effects of precise visual feedback and urgency of numerical typing were also investigated. The results showed that touch screens were as accurate as physical keyboards, but reactions were indeed executed slowly on touch screens as signified by both pre-motor reaction time and reaction time. Provision of precise visual feedback caused more errors, and the interaction between devices and urgency was not found on reaction time. To improve usability of touch screens, designers should focus more on reducing response complexity and be cautious about the use of visual feedback.

Practitioner Summary: The study revealed that slower responses on touch screens involved more complex human cognition to formulate motor responses. Attention should be given to designing precise visual feedback appropriately so that distractions or visual resource competitions can be avoided to improve human performance on touch screens.     

Older Adults’ Text Entry on Smartphones and Tablets: Investigating Effects of Display Size and Input Method on Acceptance and Performance

This study focuses on older adults’ finger-based text entry on smartphones and tablets. Thirty-two older adults entered Chinese characters with two input methods (typing and handwriting) on touch screens with four display sizes (3.5 in., 5 in., 7 in., 9.7 in.). Their performance, acceptance, preference, and errors were recorded and thus four findings were found. First, on small displays (3.5 in. and 5 in.), handwriting contributed to shorter task completion time, higher perceived ease of use, and higher usage intention than typing, but no difference was observed on large displays (7 in. and 9.7 in.). Second, there is a gap of task completion time and perceived ease of use between 5 in. and 7 in. for typing, whereas there is no gap for handwriting. Third, participants’ preference of 9.7 in. was almost the same as that of 7 in., and their preference of 7 in. was 1.5 times as strong as that of 5 in. Fourth, participants’ finger-based text entry was prone to 13 types of errors. Many of these errors were caused by the mismatch between older adults’ mental models and designers’ mental models.     

Wrist and forearm postures of users of conventional computer keyboards

The aim of this study was to perform a comprehensive investigation to document wrist and forearm postures of users of conventional computer keyboards. We instrumented 90 healthy, experienced clerical workers with electromechanical goniometers to measure wrist and forearm position and range of motion for both upper extremities while typing. For an alphabetic typing task, the left wrist showed significantly greater (p < .01) mean ulnar deviation (15.0 degrees +/- 7.7 degrees) and extension (21.2 degrees +/- 8.8 degrees) than the right wrist (10.1 degrees +/- 7.2 degrees and 17.0 degrees +/- 7.4 degrees for ulnar deviation and extension, respectively). Conversely, the right forearm had greater mean pronation (65.6 degrees +/- 8.3 degrees) than the left forearm (62.2 degrees +/- 10.6 degrees). We noted minimal functional differences in the postures of the wrists and forearms between alphabetic and alphanumeric typing tasks. Ergonomists should consider the statistically significant and probable practical difference in wrist and forearm posture between the left and right hand in ergonomic interventions in the office and in the design of computer keyboards. Actual or potential applications of this research include guiding the design of new computer keyboards.     

Productivity prediction by extrapolation: using workload memory as a predictor of target performance

In order to assess if productivity based on extrapolated data is a good predictor of longer texts, an experimental study was conducted. Two full-sized text input devices for touch typing and two miniaturized for tapping were used, all featuing QWERTY layout, in a repeated measurement design. Twenty subjects were exposed to both a task within the limit of working memory (nine words) and four running memory tasks (approx. 275 words). For miniaturized tapping keyboards, extrapolated data significantly underestimated both entry speed (uncorrected wpm, up to 17%) and character error rate (up to 61%) whereas it significantly overestimated ratio of correct words (up to 62%) of running memory tasks. Further, error-corrected entry speed was significantly overestimated up to a factor of 2.7. Results based on extrapolated productivity metrics must therefore be interpreted with caution. Running memory tasks with text length of more than 32 words is needed to assess productivity of text input devices if tapping is used.     

Productivity prediction by extrapolation: Using workload memory as a predictor of target performance

In order to assess if productivity based on extrapolated data is a good predictor of longer texts, an experimental study was conducted. Two full-sized text input devices for touch typing and two miniaturized for tapping were used, all featuing QWERTY layout, in a repeated measurement design. Twenty subjects were exposed to both a task within the limit of working memory (nine words) and four running memory tasks (approx. 275 words). For miniaturized tapping keyboards, extrapolated data significantly underestimated both entry speed (uncorrected wpm, up to 17%) and character error rate (up to 61%) whereas it significantly overestimated ratio of correct words (up to 62%) of running memory tasks. Further, error-corrected entry speed was significantly overestimated up to a factor of 2.7. Results based on extrapolated productivity metrics must therefore be interpreted with caution. Running memory tasks with text length of more than 32 words is needed to assess productivity of text input devices if tapping is used.     

Improving touchscreen keyboards: design issues and a comparison with other devices

The study explored touchscreen keyboards using high precision touch-screen strategies. Phase one evaluated three possible monitor positions: 30°, 45°, and 75° from horizontal. Results indicate that the 75° angle, approximately the standard monitor position, resulted in more fatigue and lower preference ratings. Phase two collected touch bias and key size data for the 30° angle. Subjects consistently touched below targets, and touched to the left of targets on either side of the screen. Using these data, a touchscreen keyboard was designed. Phase three compared this keyboard with a mouse-activated keyboard, and the standard QWERTY keyboard for typing relatively short strings of 6,19, and 44 characters. Results indicate that users can type approximately 25 words/minute (wpm) with the touchscreen keyboard, compared to 17 wpm using the mouse, and 58 wpm when using the keyboard. Possible improvements to touchscreen keyboards are suggested.     

Investigating touchscreen typing: the effect of keyboard size on typing speed

Two studies investigated the effect keyboard size has on typing speed and error rates for touchscreen keyboards using the lift-off strategy. A cursor appeared when users touched the screen and a key was selected when they lifted their finger from the screen. Four keyboard sizes were investigated ranging from 24.6 cm to 6.8 cm wide. Results indicate that novices can type approximately 10 words per minute (WPM) on the smallest keyboard and 20 WPM on the largest. Experienced users improved to 21 WPM on the smallest keyboard and 32 WPM on the largest. These results indicate that, although slower, small touchscreen keyboards can be used for limited data entry when the presence of a regular keyboard is not practical. Applications include portable pocket-sized or palmtop computers, messaging systems, and personal information resources. Results also suggest the increased importance of experience on these smaller keyboards. Research directions are suggested.     

Input devices for web browsing: age and hand effects

The work reported in this paper examined performance on a mixed pointing and data entry task using direct and indirect positioning devices for younger, middle-aged, and older adults (n=72) who were experienced mouse users. Participants used both preferred and non-preferred hands to perform an item selection and text entry task simulating a typical web page interaction. Older adults performed more slowly than middle-aged adults who in turn performed more slowly than young adults. Performance efficiency was superior with the mouse for older adults only on the first two trial blocks. Thereafter mouse and light pen yielded equivalent performance. For other age groups, mouse and light pen were equivalent at all points of practice. Contrary to prior research revealing superior performance with a light pen for pure pointing tasks, these results suggest that older adults may initially perform worse with a light pen than a mouse for mixed tasks.     

Wrist and forearm posture from typing on split and vertically inclined computer keyboards

A study was conducted on 90 experienced office workers to determine how commercially available alternative computer keyboards affected wrist and forearm posture. The alternative keyboards tested had the QWERTY layout of keys and were of three designs: split fixed angle, split adjustable angle, and vertically inclined (tilted or tented). When set up correctly, commercially available split keyboards reduced mean ulnar deviation of the right and left wrists from 12 degrees to within 5 degrees of a neutral position compared with a conventional keyboard. The finding that split keyboards place the wrist closer to a neutral posture in the radial/ulnar plane substantially reduces one occupational risk factor of work-related musculoskeletal disorders (WMSDs): ulnar deviation of the wrist. Applications of this research include commercially available computer keyboard designs that typists can use and ergonomists can recommend to their clients in order to minimize wrist ulnar deviation from typing.     

One-class naïve Bayes with duration feature ranking for accurate user authentication using keystroke dynamics

Biometric-based approaches, including keystroke dynamics on keyboards, mice, and mobile devices, have incorporated machine learning algorithms to learn users’ typing behavior for authentication systems. Among the machine learning algorithms, one-class naïve Bayes (ONENB) has been shown to be effective when it is applied to anomaly tests; however, there have been few studies on applying the ONENB algorithm to keystroke dynamics-based authentication. We applied the ONENB algorithm to calculate the likelihood of attributes in keystroke dynamics data. Additionally, we propose the speed inspection in typing skills (SITS) algorithm designed from the observation that every person has a different typing speed on specific keys. These specific characteristics, also known as the keystroke’s index order, can be used as essential patterns for authentication systems to distinguish between a genuine user and imposter. To further evaluate the effectiveness of the SITS algorithm and examine the quality of each attribute type (e.g., dwell time and flight time), we investigated the influence of attribute types on the keystroke’s index order. From the experimental results of the proposed algorithms and their combination, we observed that the shortest/longest time attributes and separation of the attributes are useful for enhancing the performance of the proposed algorithms.