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CHARACTER DESIGN FOR MOBILE DEVICES PDF

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character design for mobile ronaldweinland.info free download, character design for gbv - character design for mobil* devices mobile games, sprites, and pixel art. Character design in 5 Elements: The Ancient Source. Image Mage, who Indeed, thanks to the invention and development of mobile devices, at the end of the twentieth analysis/ronaldweinland.info John, F. Mobile gaming on cell phones and portable consoles is a huge business, and many characters have become design icons. However, the physical limitations of .

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UX has recently become an important topic worth consideration by top executives [ 4 ]. The goal of designing for UX is to encourage positive feelings e. Unlike usability goals, UX goals are subjective qualities and concerned with how a product feels to a user. The measurements were adopted from medical applications, such as measuring pulse and blood pressure, or using facial electromyography EMG and electroencephalography EEG to reflect computer frustration [ 13 ].

However, its validity in measuring user experience remains questionable. Although usability and UX are different, they are not completely separated. In fact, usability is part of user experience. For example, a product that is visually pleasing might evoke positive first-contact experience; however, if its usability was inadequate, it could damage overall user experience. Apart from usability, other core components of UX include useful and desirable content, accessibility, credibility, visually pleasing, and enjoyment [ 15 ].

It is the process of creating products that can be accessed by as many people as possible, with the widest possible range of abilities, operating within the widest possible range of situations [ 16 ]. To make products that can be used by everyone is impossible; however, designers can try to exclude as few people as possible, by ensuring that the products are flexible and adaptable to individual needs and preferences [ 17 ].

To accomplish universal design goals, the understanding of user diversity is needed. There are several dimensions of user diversity that differentiate groups of users. The first dimension is disabilities. Much of experimental research has been conducted to understand how disabilities affect interaction with technology. The main efforts of studies were to study the users themselves, their requirements for interaction, appropriate modalities, interactive devices, and techniques to address their needs [ 18 ].

The research includes visual impairments, auditory impairments, motor and physical impairments, and cognitive impairments [ 18 ]. Visual impairments greatly affect human interaction with technology, as human relies on vision to operate computer systems.

Visual impairments encompass a wide range of vision problems related to acuity, accommodation ability to focus on objects at different distances from the eyes , illumination adaption, perception of depth, and color vision [ 19 ].

Minor visual impairments can usually be addressed by magnifying the size of interactive elements, increasing color contrast, or selecting appropriate color combinations for color-blinded users [ 18 ]. Unlike visual impairments, blindness refers to a complete or nearly complete vision loss [ 20 ]. Blind users benefit from audio and haptic modality for input and output.

They are supported by screen readers, speech input and output, and Braille displays [ 18 ]. Auditory impairments or hearing impairments can also affect interaction with technology. The impairments may vary in degree, from slight to severe. Majority of people with hearing impairments have lost their hearing usually through aging. They have partially lost perception of frequency cannot discriminate between pitches , intensity need louder sounds , signal to noise distracted by background noise , and complexity can hardly perceive speech [ 19 ].

Some people were prelingually deaf, either were born deaf or had lost their hearing before they can speak [ 21 ]. Some strategies to address hearing impairments are to provide subtitles or captions to auditory contents or to provide sign-language translation of the contents [ 21 ]. Motor and physical impairments interfere with interaction with technology. Although causes and severity of motor impairments vary, the common problems faced by individuals with motor impairments include poor muscle control, arthritis, weakness and fatigue, difficulty in walking, talking, and reaching objects, total or partial paralysis, lack of sensitivity, lack of coordination of fine movement, and lack of limbs [ 18 , 19 ].

The main strategy to address motor impairments is to minimize movement and physical effort required for input, for instance, using text prediction, voice input, switch control devices, and eye-tracking [ 18 , 19 ]. The second dimension is age. Age influences physical qualities and abilities, cognitive abilities, and how a person perceives and processes information.

The elderly and children are the two major age groups that have age-dependent requirements [ 18 ]. There are several definitions of children. Some studies include adolescence 13—18 years into childhood, whereas some studies focus only on children under the age of 12 [ 18 , 22 ]. Like the children group, there is no consensus on the cut-off point of old age. Most researchers regard 55 years as the beginning of old age.

Nevertheless, there are enormous differences in abilities and problems within elderly group; for example, people aged 55 and people aged 90 are extremely different [ 19 ]. Therefore, the age range is further divided into two or three groups: young-old ages 55 to 75 and old-old over 75 or young-old ages 65 to 74 , old-old ages 75 to 85 , and oldest-old over age 85 [ 19 ].

Old age is associated with declines in vision, hearing, motor function, and cognition [ 19 ]. Elderly people commonly have problems with vision acuity, depth of perception, color vision, hearing high frequency sounds, controlling coordination and movement, short- and long-term memory, and information processing speed [ 19 ].

Children have unique characteristics. They do not possess the same levels of physical and cognitive capabilities as the adults. They have limited motor abilities, spatial memory, attention, working memory, and language abilities. Thus, the general characteristics of the elderly and children need to be considered when developing products for these two age groups. The third dimension is culture. Cultural differences include date and time format, interpretation of symbols, color meaning, gestures, text direction, and language.

Thus, designers must be sensitive to these differences during the development process and avoid treating all cultures the same [ 18 ]. The fourth dimension is computer expertise. Some groups of users are unfamiliar with technology, for example, older adults and those with minimal or no education. Some strategies to address differences in expertise level include providing help options and explanations, consistent naming convention to assist memory, and uncluttered user interface to assist attention [ 18 ].

Mobile Computing The first era of mobile devices dated back to the late s and early s. The focus of this era was to reduce the size of computer machine to support portability [ 23 ]. Mobile phones introduced during this period were still large and required enormous batteries [ 24 ]. Around ten years later, mobile devices reached the point where the sizes were small enough to be fit in a pocket. During the same time, the network shifted to 2G technology and cellular sites became denser; thus, mobile connectivity was easier than before.

This led to the increase in consumer demand for mobile phones. Increased demand meant more competition for service providers and device manufacturers, which eventually reduced costs to consumers [ 24 ].

In the late s, feature phones were introduced to the market. Smartphone era started around Smartphones have the same capabilities as the feature phones; however, the smartphones use the same operating system, have larger screen size, and have a QWERTY keyboard or stylus for input and Wi-Fi for connectivity [ 24 ].

The most recent era starts in when Apple launched the iPhone [ 23 , 24 ]. It was like smartphones; however, it presented a novel design of mobile interactions. It introduced multitouch display with simple touch gesture e. The iPhone was also equipped with context-awareness capabilities, which allowed the phone to detect orientation of the phone, or even the location of the users. It took a couple of years later for the competitors to match up with the Android operating system, mobile devices, and associated application store [ 23 ].

The challenges of mobile interaction and interface design have evolved over time.

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Early mobile interaction design involved physical design, reducing physical size while optimizing limited screen display and physical numeric keypads [ 23 ].

Later, the challenges evolved to the development add-on features, for example, digital cameras and media player. However, today challenges may have moved to a completely new dimension. Physical shape and basic size of mobile phones have remained unchanged for many years. The challenges may have shifted to the development of software application or designing mobile interaction [ 23 ].

Previous Reviews There have been several previous reviews of mobile user interface; however, they did not focus on user interface design patterns. Instead, the focus was primarily on certain application domain of mobile devices. For instance, Coppola and Morisio [ 25 ] focused on in-car mobile use. Their article provided an overview of the possibilities offered by connected functions on cars, technological issues, and problems of recent technologies. They also provided a list of currently available hardware and software solutions, as well as the main features.

Pereira and Rodrigues [ 26 ] made a survey on mobile learning applications and technologies. The article provided an analysis of mobile learning projects, as well as the findings of the analysis.

Becker [ 27 ] surveyed the best practices of mobile website design for library. Monroe et al. Donner [ 29 ] reviewed mobile use in the developing world.

His article presented major concentrations of the research, the impacts of mobile use, and interrelationships between mobile technology and users.

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Moreover, the article also provided economic perspective on mobile use in the developing world. Some review articles concentrated on technical approach of mobile devices and user interface. For instance, Hoseini-Tabatabaei et al. Their article provided introduction to typical architecture of mobile-centric user context recognition, the main techniques of context recognition, lesson learned from previous approaches, and challenges for future research.

Akiki et al. The article addressed the strengths and shortcomings of architectures, techniques, and tools of the state of the art. Summary of the evaluation, existing research gaps, and promising improvements were also stated. Cockburn et al. Critical features of the four approaches and empirical evidence of their success were provided.

Some previous reviews focused on mobile use in some user groups. For instance, Zhou et al. Their article provided a summary on technology acceptance of the elderly users, input devices, menus and functions, and output devices. Some more reviews concerned the impact of mobile use.

Moulder et al. The article provided summary from relevant medical research. Nevertheless, the evidence for a causal association between cancer and radiofrequency was weak and unconvincing.

Research Questions This article surveys literature on usability studies on mobile user interface design patterns and seeks to answer the following two research questions: RQ1: in each area, what factors were concentrated? RQ2: what areas of mobile user interface design patterns had insufficient information?

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Literature Search Strategy Four phases were used to systematically survey literature: 1 listing related disciplines, 2 scoping databases, 3 specifying timeframe, and 4 specifying target design elements.

Listing Related Disciplines The first phase was to list out HCI related disciplines, to cover user interface research from all related disciplines. Based on [ 3 , 35 ], the related disciplines are as follows: computer science and engineering, ergonomics, business, psychology, social science, education, and graphic design.

The databases covered all disciplines mentioned in Section 5. Table 1: Database list. Specifying Timeframe The current article was confined to the papers published from to As stated, many companies released new touchscreen mobile devices in , which was a turning point of research attention [ 5 , 6 ]. Specifying Target Design Elements The categories of major design patterns defined in the book Designing Mobile Interfaces, by Hoober and Berkman [ 7 ], were used to scope literature search.

The categories were listed in Table 2. Table 2: Design patterns and subelements. There were altogether 10 categories of mobile UI design patterns. Some of them contained subelements; for instance, in input mode and selection, the subelements of this category were gesture, keyboard, input area, and form.

The subelements in the categories were also included in retrieval keywords. The abstracts of all retrieved papers were initially read through. The number of primary search results and the remaining papers in each category were listed in Table 3.

Table 3: Primary search results and remaining papers in each category. From Table 3 , the input mode and selection category had the highest remaining papers—27—followed by icons 14 papers , information control 9 papers , buttons 7 papers , page composition, display of information, and navigation 4 papers each. The control and confirmation, revealing more information, and lateral access categories had no relevant papers.

In each category, the papers which shared the common ground were grouped together, to posit research theme in each design pattern. Research Overview This section provided an overview of prior research and studies on each category of mobile UI design pattern conducted since Page Composition Page composition is a very broad term for interface design.

A composition of a page encompasses various components, including scrolling, annunciator row, notification, title, menu patterns, lock screen, interstitial screen, and advertising [ 7 ]. Only menu was discussed in this section. The other elements that were overlapped with other topics would be discussed later i.

Menu method is a popular alternative to traditional form of retrieving information [ 36 ]. It plays a significant role in overall satisfaction of mobile phones [ 37 ]. The primary function of menus is to allow users to access desired functions of applications or devices. Early research on menus was carried out on many topics. The research primarily examined effectiveness of menu patterns and relevant components on desktop platform.

The research included 2D and 3D menus, menu structures depth versus breadth , menu adaptation, item ordering categorically and alphabetically , item categorization, task complexity, menu patterns hierarchical and fisheye , help fields, methodological studies, and individual differences [ 36 ]. The first few studies of menus on mobile devices are due to small screen of devices. The guidelines or principles that are generally applied from menus on personal computers should be reexamined.

Early studies on desktops show that 3D menus can convey more information than 2D menus. In mobile context, superiority of 3D menus can be inconclusive as the screen size is more limited. The performance of menus was measured by task completion time, satisfaction, fun, and perceived use of space. The results partially substantiated previous studies.

With respect to overall metrics, 3D menus outperformed 2D menus; however, the 2D menus surpassed 3D in high breadth level [ 36 ]. In fact, there are more types of 2D and 3D menus that have not been examined, and they can be further studied. Besides menu components, prior research showed that user factors had influences on menu usability. The topics included user language abilities, spatial abilities, visual characteristics, and user expertise [ 36 ]. The scope became narrower and it examined primarily on age and cultural differences since Prior research highlighted cultural influences on usability.

The research was mostly at superficial level e. Moreover, they were mostly conducted in desktop environment [ 38 ]. Thus, applying the findings from desktop research to mobile environment remained unsettled.

Kim and Lee [ 38 ] examined correlation between cultural cognitive styles and item categorization scheme on mobile phones. They found different user preferences towards categorization of menu items. Dutch users representing Westerners preferred functionally grouped menus, for instance, setting ringtones and setting wallpaper, as they shared a common function—setting.

In contrast to Dutch users, Korean users representing Easterners preferred thematically grouped menu, for instance, setting wallpaper and display, as they shared a common theme—pictorial items. Apart from cultural differences, influence of age differences on menu usability was also studied. As people aged, there are changes and decline in sensation and perception, cognition, and movement control, for instance, decline in vision acuity, color discrimination, hearing, selective attention, working memory, and force controls [ 39 ].

These changes influence computer use. Thus, user interface must be designed to support the unique needs of older users. A study found that aging had influences on menu navigation. Menu navigation is an important concern when designing a menu, as an effective menu leads users to correct navigational path. Effective menu is related to several components, including the structure of the menu, its depth and breadth, and naming and allocation of menu items.

Menu navigation is also associated with individual factors: spatial ability, verbal memory, visual abilities, psychomotor abilities, and self-efficacy, and these individual factors are age-related [ 40 ].

Menu navigation is more challenging on mobile devices, as the menus are implemented on limited screen space and users can partially see the menus; thus, users need to rely on working memory more than on desktops. The performance of menu navigation was measured by task completion time, number of tasks completed, detour steps, and node revisited. The results of the preliminary tests indicated that spatial ability, verbal memory, and self-efficacy of younger users were significantly higher than older users.

Task completion time, number of tasks completed, detour steps, and nodes revisited of older users were significantly greater than those of younger users; in other words, younger users outperformed older users on mobile menu navigation [ 40 ].

However, further analysis found that the variable which had the best predictive power for navigation performance was not age but spatial ability; age was only a carrier variable that was related to many variables which changed over the lifespan. Although all older users in their study were experienced computer users, the study found that more than half of them were not able to build a mental model of how the system was constructed. Their study also found that both verbal memory and spatial ability were related to strategies employed in menu navigation.

Users with high spatial ability navigated through information structure based on their spatial representation of menu structure, while users with high verbal memory referred to memorization of function names in navigation [ 40 ].

With many individual factors and diversity of users, one-size-fits-all system is impossible to achieve, and tailoring product to fit all segments of users is very costly. An alternative solution is to allow users to adapt the interface adaptable interface or to allow the interface to adapt itself adaptive interface. Both types of interfaces locate frequently used items in a position that can be easily selected by the users; thus, menu selection time can be reduced [ 41 ].

However, each of them has its own weaknesses. On adaptive interface, no special knowledge of users is required, as the interface can adapt itself; however, users can have difficulty in developing mental model of the system due to frequent change of item location. On adaptable interface, users can autonomously manipulate location of items, but users need to learn how to move items to intended position [ 42 ]. Prior studies on desktops show that adaptive interfaces have potential for reducing visual search time and cognitive load, and adaptive interfaces can be faster in comparison to traditional nonadaptive interfaces [ 43 ].

Nevertheless, these two approaches have been less studied on mobile devices. Park et al. The study found that the traditional menu had higher learnability as the menu items did not change their positions.

However, the traditional menu did not provide support for frequently selected items, and this type of menus became less efficient when the number of items was large. Adaptable menus were more robust but required a significant amount of time to learn adaptation and to memorize which items to adapt. The adaptable menu with highlights on recently selected items helped users recognize which items should be adapted. Performance of the adaptive menus was similar to the adaptable one; however, constantly changing item locations made it difficult for users to develop stable mental representation of the system.

In sum, the results showed that adaptable menu with highlights were in favour by most users, as the highlights could reduce memory load for adaptation [ 44 ]. Display of Information On desktops, users are constantly surrounded by ocean of information. Many information display patterns help users in filtering and processing relevant visual information. Examples of information display patterns include different types of lists, including vertical list, thumbnail list, fisheye list, carousel, grid, and film stripe [ 7 ].

Limited screen size has caused a design challenge to information display patterns and effectiveness of applying desktop designs to mobile platform unsettled. Since , research has been directed to reassessment of display pattern usability, specifically on efficiency, error rate, and subjective satisfaction. In [ 45 ], the fisheye list was compared to the vertical list on satisfaction and learnability, which was measured in terms of task execution time in this study.

The study was carried out with 12 participants, aged 10 to The results showed that the vertical list was better than the fisheye menu in task execution time; thus, the vertical list was superior to the fisheye list in terms of learnability. Despite being more efficient, the vertical list was less preferred as the fisheye menu was more visually appealing [ 45 ].

Another study compared a list-based to a grid-based interface on click-path error and task execution time. The two layouts were very common on mobile devices [ 46 ]. He ran the experiment with 20 participants, who were experienced mobile phone users, and all of them were students, staffs, or faculty members of the university. The results showed that grid-based interface was significantly more efficient, and it was rated as more appealing and more comfortable by the users [ 46 ].

Besides the layouts, there has been an argument that interaction concepts established on desktops work only with restrictions [ 47 ]. Due to limited screen size, list scrolling and item selection can be more demanding on mobile devices than on desktops.

Breuninger et al. The seven types of list included 1 scrollbar, 2 page-wise scrolling with arrow buttons, 3 page-wise scrolling with direct manipulation, 4 direct manipulation of a continuous list with simulated physics, 5 direct manipulation of a continuous list without simulated physics, 6 direct manipulation of a continuous list with simulated physics and an alphabetical index bar, and 7 direct manipulation of a continuous list without simulated physics and with an alphabetical index bar.

The results indicated that there were variations in efficiency of different list scrolling mechanisms.

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Although the differences between other interaction types were not significant, participants most preferred direct manipulation with simulated physics [ 47 ]. To compensate difficulty of input precision, interaction with mobile devices was sometimes done through a stylus, pressure sensing, or alternative interaction styles. The experiment asserted that the Zoofing technique outperformed conventional scrolling interaction on selection time and input errors [ 48 ].

Control and Confirmation Physical and cognitive limits of human users often cause unwanted errors that can be trivial to drastic. On computer systems, control and confirmation dialogues are being used to prevent errors, typically user errors. A confirmation dialogue is used when a decision point is reached and user must confirm an action or choose between options. Control dialogue is used to prevent against accidental user-selected destruction, for example, exit guard and cancel and delete protection [ 7 ].

Since , there has been no research regarding control and confirmation dialogues on mobile devices. Revealing More Information Two common types for revealing more information are to display in a full page and revealing in a context. Revealing in a full page is generally part of a process, where large amounts of content will be displayed. Revealing in context is generally used when information should be revealed quickly and within a context.

Some of the patterns for revealing more information include pop-up, window shade, hierarchical list, and returned results [ 7 ]. Since , there has been no research regarding patterns in revealing more information on mobile devices. Lateral Access Lateral access components provide faster access to categories of information. Two common patterns for lateral access are tabs and pagination. There are several benefits of using lateral access, including limiting number of levels of information users must drill through, reducing constant returning to a main page, and reducing the use of long list [ 7 ].

Since , there has been no research regarding lateral access on mobile devices.

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Navigation Links A link is a common element available on all platforms. It supports navigation and provides access to additional content, generally by loading a new page or jumping to another section within the current page [ 7 ]. Early research was primarily conducted on desktop environment and mainly supports web surfing.

Navigation on small screen of mobile devices can be more challenging. Typical web navigation technique tends to support depth-first search. In other words, users select a link on a page, then a new page would be loaded; and the process would repeat until the users find the information they need [ 49 ].

This method is more difficult on mobile environment, as the navigation is constrained by small screen size. It was found that search behavior on mobile device was different from that on desktop. Most mobile users used mobile devices for directed search, where the objective was to find a predetermined topic of interest with minimum divergence by unrelated links [ 49 , 50 ].

Some alternative solutions to tackle this issue were to show a thumbnail of the page [ 51 ]. However, the thumbnail approach may benefit only desktops. Thumbnail is a scaled down version of the target page. Thus, it contains exceeded unnecessary amount of information when displayed on mobile screen. An alternative method may be needed for mobile devices. Setlur et al. SemantiLynx automatically generated icons that revealed information content of a web page, by semantically meaningful images and keywords.

User studies found that SemantiLynx yielded quicker response and improved search performance [ 49 , 50 ]. Another challenge to navigation on mobile devices is to display large amount of information on a small screen. Large amount of information makes it more difficult for users to navigate through pages and select information they need. Early research on desktop employed gaze tracking technique to utilize navigation; however, peripheral devices and software were required in this approach [ 52 ].

Cheng et al. The performance on the prototype was satisfactory; however, comparison to conventional navigation technique was still lacking.

Another challenge for mobile interaction is the need for visual attention [ 54 ]. As stated, contexts of use of desktop computers and mobile devices are different.

Desktop computers are always stationary, whereas mobile device is ubiquitous. Users can use mobile devices while doing some other activities, such as walking, carrying objects, or driving. This brings about inconvenience when users cannot always look at the screen. Aural interface or audio-based interface is an alternative solution.

Users can listen to the content in text-to-speech form and sometimes look at the screen. However, it is difficult to design aural interface for large information architecture. Backtracking to previous pages is even more demanding, as users are forced to listen to some part of the page to recognize the content.

Yang et al. In topic-based backnavigation, the navigation went back to visited topic, rather than visited pages. In list-based backnavigation, the navigation went back to visited list of items, rather than visited pages. The study found that topic-based and list-based backnavigation enabled faster access to previous page and improved navigation experience. Buttons Button is one of the most common design elements across all platforms. It is typically used to initiate actions i.

Early research covered several topics, including button size and spacing, tactile and audio feedback, and designing for users with disabilities [ 55 — 58 ]. Since , research direction has been strongly influenced by touchscreen characteristics. Touchscreen enabled more versatility in interface designing as a large proportion of the device is no longer occupied by physical buttons; however, this brings about a new design challenge—the lack of physical response and tactile feedback.

Without physical responses, users have less confidence on the consequences of their actions which eventually compromise system usability [ 59 ]. Studies indicated that tactile feedback improved efficiency, error rate satisfaction, and user experience [ 60 ].

Nevertheless, not all types of the feedback are equally effective. There are certain factors that contribute to tactile feedback quality. The first factor is the realistic feel of physical touch. The results found that participants preferred the clear or smooth tactile clicks over dull ones for virtual buttons [ 59 ]. Besides the realistic feel of physical touch, simultaneity of touch-feedback and the effects of latency is another factor that influences tactile feedback quality.

In [ 58 ], latency was varied from 0 to ms. The results showed that long latency worsened perceived quality. The perceived quality was satisfactory when latency was between 0 and ms. When the latency condition was ms. Koskinen et al. They compared three conditions of virtual button feedback— 1 Tactile and audio, 2 tactile and vibration, and 3 nontactile—to find the most preferred style of feedback.

The results suggest the using nontactile feedback was least preferred by the users. It also yielded the lowest user performance which was measured by time to complete tasks and error rate.

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Tactile and audio feedback was more pleasant and better in user performance than the tactile and vibration one; however, the differences were not significant [ 60 ].

Another challenge is the high demand for visual attention. As stated, mobile devices are designed for ubiquity. Users may need to do some other activities simultaneously while using the devices.

Pressing virtual buttons can be more difficult, and incorrect operations can occur more frequently as users need to divide their attention to the environment. To compromise high error rate, studies on spatial design of virtual buttons were carried out to explore the appropriate button size, spacing between buttons, and ordered mapping of buttons [ 55 — 57 ]. Conradi et al. Walking also had a significant influence on errors for all button sizes.

The influence was magnified with smaller buttons. The findings of this study suggested that larger buttons were recommended for the use while walking [ 56 ]. Haptic button is another approach to tackle the challenge. Pakkanen et al. The stimuli in the simple design were accompanied with single bursts, and identical stimuli were utilized whether towards or away from the buttons.

GUI transformation stimuli were combined with several bursts. When moving over the edge, the burst raised from the minimum to maximum, and the burst decreased from maximum to minimum when moving away from the edge. In designed stimuli, when moving off the button, there was a single burst which simulated slipping off the buttons. The results indicated that simple and designed stimuli were most promising.

Furthermore, stimuli with fast, clear, and sharp responses were good choice for the haptic button edge. Another complementation for the demand for visual attention is to utilize physical buttons, such as a power-up button [ 62 ]. Spelmezan et al. Even though the preliminary experiment yielded promising results, the prototype required the installation of additional sensors: proximity sensor, and pressure sensor [ 62 ].

Besides the lack of tactile feedback and demand for visual attention, touching gesture can be hard for users with fine motor disabilities. Pressing a small size button requires high precision in fine motor control, and different contact time on buttons may alter actions e. Sesto et al.

The results showed that touch characteristics were affected by the button size, but not spacing. The users with fine motor disability had greater impulses and dwell time when touching buttons than nondisabled users. The findings of this study can guide designers in designing an optimal size and touch characteristics to enhance accessibility of virtual button [ 55 ].

Icons An icon is a visual representation that provides users with access to a target destination or a function in a cursorily manner [ 7 ]. Icons serve altogether three different functions. Those functions are 1 an access to a function or target destination, 2 an indicator of system statuses, and 3 a changer of system behaviors [ 7 ]. The topics of early research extended to various areas, including the use of icons to convey application status; interpretation of icon meaning, icon recognition, and comprehensibility of icons; appropriate size of an icon; and influences of cultural and age differences on icon interpretation [ 63 — 65 ].

Since , research has been directed to two major areas: icon usability and influences of individual differences age and culture.

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