Human-Computer Interaction. Interaction Technologies

One character is entered with two steps: firstly, selecting a group of five characters, and secondly selecting one character from the group. For Japanese Hiragana letters, each row of a table of the Japanese syllabary, is used as the group. For alphabets, every five letters in alphabetical order are gathered to one group.Each of the left edge, the upper edge, and the right edge of the screen is divided into two segments. A pair of groups is assigned to each of the segment. The group is selected by slide-in. The slide-in is the operation that first touch a finger to the outside of the screen then move it inside the screen as it is. Since the fingertip definitely passes through the edge of the screen during the slide-in, the crossing can be detected with the area which width is only 2 mm. Therefore, 73.6% of the screen can be used for displaying text if the size of the screen is 1.63 in. When the group is selected, the screen is divided to $$ 3 \times 3 $$ blocks and 5 characters of the group are displayed there. By tapping on one character, it is entered.In the experiment, beginners entered characters at a speed of 28.7 [CPM] in average, after 5.3 min usage in total. The input speed of an expert is 67.7 [CPM]. In another experiment entering 10 words a day, the input speed exceeded 50 [CPM] after 30 days, when total time of use is 39.5 min.

Convenience stores are almost everywhere, offering a modern part of life. Convenience stores in Taiwan also serve as links to the world where you can pay gas bill or even get tickets for a concert through the self-service Multi Media Kiosks (MMK). Self-service Multi Media Kiosks (MMK) were set up by domestic convenience stores (i-bon, FamiPort, Life-ET, OK·go) in Taiwan, offering on line services like payment, value-adding, ticket booking and others. Nevertheless, with more and more services provided through MMK, too many options in the main menu often confuse users and usability problems arise. Shortcuts enables users quickly start common or recommended tasks within MMK’s main menu. One of the effort to improve the problem in main menu is to define shortcuts to specific actions according to prevailing tasks among users. Unfortunately, the pilot study remarked that half of the users didn’t notice the presence of accessible shortcut options. For this reason, this study intended to validate effectiveness of shortcuts setting and assume that page layout and number of selection keys are essential to user’s visual search efficiency. To achieve the goal, an innovative MMK’s main menu prototype was developed by adapting the layout and option features following visual search theories of subitizing effect that suggest a clear limit in the accuracy of numerosity judgements was found to be set at 4. Limit number of allowed selections in one page did challenge the hierarchical structures of MMK’s content management but was worth trying. In the proposed prototype, eight recommended shortcut options were set quaternary groups in the first page of MMK user interface, followed by (responsively disclosed) content of main menu, in which, quaternary groups layout was employed again. The usability evaluation of proposed prototype was completed by users experiment. Research findings include: (1) For those participants aiming to reach the prevailing tasks, the utility rate of enhanced features shortcut options was promoted to 100%. (2) For those participants aiming to reach the non-prevailing tasks, although having to go through shortcut options page and then shift to main menu, the average operation time is not slower than that of two existing MMK systems with lower error rate. The result indicated that subitizing effect works!

Ultra-small touch screen devices (e.g., smartwatches) are required to be small and lightweight so that they can be worn on the body with no frustration. For this reason, users often have difficulties in selecting the correct keys, and thus entering texts. Therefore, entering texts on ultra-small touch screen devices is impractical. To address this problem, we present Flickey, a flick-based QWERTY software keyboard for ultra-small touch screen devices. The flick-based selection mechanism of Flickey, in combination with its callout technique, allows users to select a tiny key on the small keyboard more easily than with a tap. To investigate the performance and usability of Flickey, we developed a prototype of Flickey and conducted a comparative experiment with two existing keyboards. The results suggest that Flickey shows high performance when the size of the keyboard becomes small.

In recent years, virtual reality is becoming popular with the advent of PlayStation VR and mobile VR. However, due to the restrictions of the hardware, it is difficult to reproduce the same thing in the virtual space, as it is in the reality. One of the typical examples is the character input. It is extremely difficult to reproduce convenience and speed equivalent to traditional used input methods such as personal computer keyboard input or smartphone flick input, in the virtual space. Therefore, in this study, we aim to propose a new character input method, focusing on typing Japanese characters, which has an input speed at a certain level, is touch-typable, and requires no controller in a user’s hands. The proposed approach uses Leap Motion as an input device. By tracking the movements of the finger of a user, the user selects a pair of a consonant and a vowel with two bending and stretching movements, which makes a Japanese letter. From a preliminary experiment, our method achieved the input speed of 42.1 Characters per Minute. In addition, this paper discusses the duration of the practice needed to use this method.

This paper proposes a system that types the virtual keyboard by recognizing hand gestures in a single camera based environment. A virtual keyboard is designed in a multi-tab method of 3 × 4 arrays that are widely used in a mobile environment. In order to make it easy to identify the type-in action and consequently, to increase the type-in speed, this paper proposes a new definition of type-in action as the contact between the thumb and the index finger. To further reduce the input time, the keyboard layout is optimized by efficiently arranging alphabet keys according to the frequency of character appearance. Experimental results show that the proposed type-in action is effective to give commands with a virtual keyboard. Furthermore, the proposed keyboard layout achieves the speed-up by an average of 46.16% compared to the most conventional ‘ABC’ keyboard.

We describe a method termed Ex-Space to enable continuous, one-dimensional keyboard input on the home position. The method features thumb movement on the space key. We developed a prototype of the method consisting of a piece of conductive fabric attached to the space key to detect the position of the sliding thumb. In addition, we performed two preliminary experiments: an experiment to calculate the resolution afforded by touch position detection, and an experiment to explore the performance of menu command input using Ex-Space.

We developed a method to enter Hiragana (cursive in Japanese) characters and alphanumeric characters by thumb gestures for Japanese people. This method is optimized to be used while holding the left and right ends of a tablet PC with hands. Each gesture is designed by concatenating a few horizontal and/or vertical strokes, but path of the gesture remains inside the one-stroke square centering its starting position. A Hiragana character is input by selecting a row of the table of Japanese syllabary and then a column of the table. The alphabet characters are segmented into 6 groups in order of letters. Just like Hiragana, an alphabet character is entered by selecting a group and then selecting a member. However, in the alphanumeric mode, to reduce the cost of modifying the mistakenly selected group, an operation to move to the previous or next group have been added. Characters are entered by gestures executed by the dominant hand. Gestures carried out in the opposite hand are assigned to some control codes that are needed to kana-to-kanji conversion and document modification. Since the input guide on the display is rewritten each time when one stroke is recognized, a user can enter any character by moving the thumb to the direction of the character shown on the guide, even if he or she does not memorize its gesture.In the experiment entering Hiragana, input speed of beginners was about 20 [CPM]. A person skillful at this method could input about 58 [CPM] without watching fingertips.

With the increasing use of mobile phones and tablets and the widespread use of internet networks, the use of applications designed for these platforms is increasing. Users generally have to input various types of data while using these applications and specifying date is one of the input types. In the scope of this study, a user study with 10 participants was conducted to compare four different input methods, which were used for specifying dates in mobile forms. Four different input methods were textbox, divided textbox, datepicker and calendar view. Time required to complete date entry tasks and errors occurred during these tasks were recorded and participants’ preferences were gathered. Textbox was found to be the fastest and most accurate input method while calendar view was the slowest and most error prone. In addition, participants preferred divided textbox the most.

This work presents some initial results of our research about the design and implementation of “LiSA” (Link Student Assistant), a chatbot intended to help students in their campus life, through information and services. The focus of our research is to understand which kind of information and services are better accessed through this kind of touch point, how the chatbot personality influences the user experience and the interaction and which level of intelligence should be implemented. After an analysis of the state of the art in the considered application domain we investigated, through a survey, the users’ needs and their inclination to the use of a chatbot for this specific purpose. A chatbot was created to deliver the survey, allowing to understand both the users’ needs and their behaviour while using the tool.

With the development of artificial intelligence, autonomous vehicle as a new form of driving comes into public view. In this new Human-Machine Interaction Model, relationship between people-vehicles and user mental model have met a great change which include the information process, sequence, sorting, information architecture, navigation, visual thinking, data visualization, interface and media design. Autonomous vehicle uses the artificial intelligence and driving big data in the Intelligent Transportation System to deal with the cognition and perception, builds new paradigm for the human-machine interaction. The mental model based on human perception and cognition is not suitable for the mental model based on artificial intelligence. To enhance the user experience, the paper presents the hybrid mental model which combine the human mental model and AI mental model, consequently analyzes the user experience and interaction design influenced by mental model which is driven by human intelligence and artificial intelligence in the traditional mode and the autonomous vehicle mode. Based on Induction and Comparative Study on different mental models, the paper concludes the advantages and disadvantages of visual and auditory channels in autonomous vehicle. Finally, the paper presents the principles of voice user interface design in the view of adaption to the new environment, meeting the gap of the needs of users’ satisfaction of control and privacy protection, defines the usability targets and user experience targets for the autonomous vehicle voice user interface design.

Speech interaction as one of the contact-free input techniques has been applied in mobile devices (e.g. smartphone) for many years, which means that a considerable number of users were exposed to speech interaction. In China, speech interaction, while undoubtedly natural, has also entered users’ life for more than 5 years but it is still perceived as “not that good”. Curiosities are stimulated that what barriers are that prevent speech from becoming one of the mainstream interaction modality in China, yet there is no research on the user experience of mobile speech interaction. An online questionnaire was used to measure participants’ speech interaction use of smartphone. Simple Logistic Regression Model and Ordinal Logistic Regression Model were used as the primary method of data analysis. This study concluded that speech interaction is an interactive modality for the future and need to give full play to the advantages of speech interaction by reducing interface exclusivity, offering services to users actively in combination with situational awareness and guiding users in a variety of modalities.

Machine operators remain important in future production environments and need intuitive and powerful interaction techniques. Many assistance and support applications for machine operators use speech-based interfaces since they are suitable during manual tasks and when visual attention cannot be occupied. Due to developments like the demographic change or the need for skilled personnel, the skills and capabilities of the workers will become increasingly diverse. Speech-based interfaces therefore need to be adaptable to the capabilities, limitations and preferences of individual operators. This paper addresses this requirement and proposes an adaptive speech interface that supports machine operators during maintenance and changeover procedures. All aspects of the proposed application can be adapted to the requirements of the user. The system uses a process model, instruction templates, a user model, and a model of the input vocabulary to describe the components of the application. This allows a flexible adaptation of the speech interface and the provided instructions to the requirements of individual users and to further use cases.

To generate action events for a humanoid robot for human robot interaction (HRI), multimodal interactive behavioral models are typically used given observed actions of the human partner(s). In previous research, we built an interactive model to generate discrete events for gaze and arm gestures, which can be used to drive our iCub humanoid robot [19, 20]. In this paper, we investigate how to generate continuous head motion in the context of a collaborative scenario where head motion contributes to verbal as well as nonverbal functions. We show that in this scenario, the fundamental frequency of speech (F0 feature) is not enough to drive head motion, while the gaze significantly contributes to the head motion generation. We propose a cascaded Long-Short Term Memory (LSTM) model that first estimates the gaze from speech content and hand gestures performed by the partner. This estimation is further used as input for the generation of the head motion. The results show that the proposed method outperforms a single-task model with the same inputs.

This paper investigates the effect of speaking rate variation on the task of frame classification. This task is indicative of the performance on phoneme and word recognition and is a first step towards designing voice-controlled interfaces. Different speaking rates cause different dynamics. For example, speaking rate variations will cause changes both in formant frequencies and in their transition tracks. A word spoken at normal speed gets recognized more often than the same word spoken by the same speaker at a much faster or slower pace, or vice-versa. It is thus imperative to design interfaces which take into account different speaking variabilities. To better incorporate speaker variability into digital devices, we study the effect of (a) feature selection and (b) the choice of network architecture on variable speaking rates. Four different features are evaluated on multiple configurations of Deep Neural Network (DNN) architectures. The findings show that log Filter-Bank Energies (FBE) outperformed the other acoustic features not only on normal speaking rate but for slow and fast speaking rates as well.

This paper presents an online chat interface design which can display users’ mixed emotions during online chatting in the form of gradient color. This design is based on affective recognition and tries to provide an effective way of emotional communication. The system of this design consists of two parts: emotional recognition and emotional display. The affective recognition function relies on the Microsoft cognitive service, which provides APIs (Application Programming Interface) to make the function quick and accurate. Mixed emotions are shown by gradient color and an emotion indicator has been added to create an emotional chatting environment. A preliminary test has been done among 8 couples or lovers to evaluate the design and the results show that this online chat interface design, which aims to help mixed emotional communication, can be useable for lovers chatting. The study provides opportunities for further improvement and exploration of this approach and applications to more fields.

We present a dynamic framework for the integration of Machine Learning (ML), Augmented Reality (AR), Affective Computing (AC), Natural Language Processing (NLP) and Computer Vision (CV) to make possible, the development of a mobile, sympathetic, ambient (virtual), augmented intelligence (Agent). For this study we developed a prototype agent to assist photographers to enhance the learning and creation of photography. Learning the art of photography is complicated by the technical complexity of the camera, the limitations of the user to see photographically and the lack of real time instruction and emotive support. The study looked at the interaction patterns between human student and instructor, the disparity between human vision and the camera, and the potential of an ambient agent to assist students in learning. The study measured the efficacy of the agent and its ability to transmute human-to-Human method of instruction to human-to-Agent interaction. This study illuminates the effectiveness of Agent based instruction. We demonstrate that a mobile, semantic, sympathetic, augmented intelligence, ambient agent can ameliorate learning photography metering in real time, ‘on location’. We show that the integration of specific technologies and design produces an effective architecture for the creation of augmented agent-based instruction.

In this paper, we introduce a remote co-shopping system–Shopping Together for two geographically separated people: an in-house user who remains in a house and an in-store user who goes to a shopping place. We support the two of users to achieve a real-time two-way spatial gestural interaction in the physical shopping world where the in-store user stays, with an attention awareness subsystem to enhance a common feeling. The in-house user accesses to the remote shopping venue with an immersive shopping feeling, while the in-store user experiences an augmented reality feeling. Through our system, users could accomplish a shopping task together and share a Shopping together feeling which means a sensation that they are going for purchase together in the same space.

We conducted a user study comparing the accuracy and speed of two zooming methods for touch-screen devices: tap-and-drag (a single-handed zooming method) and the traditional pinch-to-zoom (performed with one hand). The study involved 12 participants and employed a Google Pixel 2 mobile phone. The results for task completion time favored tap-and-drag, which was about 18% faster than pinch-to-zoom. The accuracy results for tap-and-drag were slightly lower with an average accuracy of 84.8% compared to 87.9% for pinch-to-zoom. This was attributed to users being unfamiliar with tap-and-drag. As users became more familiar and comfortable with tap-and-drag, accuracy improved. Tap-and-drag was about 47% more efficient than pinch-to-zoom, with efficiency measured as the number of gestures to complete a trial. Participants indicated a preference for tap-and-drag for one-handed zoom gestures.

In this study, we examine the effectiveness of a female-clothing coordination-generation system using eye-tracking information for multiple users. In our previous study, only two subjects used an interactive evolutionary computation (IEC) system by utilizing the users eye-tracking information, which however poses two issues for actual application. First, the number of subjects simultaneously using the system was low. Moreover, they were given specific instructions on how to use the system in advance. To solve these issues, we review our previous method, and develop a female-clothing coordination-generation system using digital signage and verify its effectiveness. The experimental results demonstrate that the system can simultaneously create satisfactory clothing coordination for multiple users.

With the increasing number of functionalities of In-Vehicle Information Systems (IVIS) their complexity is rising. In addition new input modalities are used to control the car. Many manufacturers switch from using haptic input devices to touchscreens. On the other hand there are increasingly more sensors available in a car that could support the driver in their interaction with an IVIS by analyzing the driver’s behavior. In this study gaze behavior prior to an interaction with was analyzed. Therefore 32 participants completed different tasks with an IVIS in a high-fidelity driving simulator. While driving, the participants were asked to navigate to a specific entry in a multi-level menu. Task and driving difficulty were modified as well as the input modality. One experimental group used a touchscreen and another one a rotary knob. Between the tasks, a short status information was presented to the participant either auditory or on a display. In 60.19% of the interactions, at least two preparatory glances were made. When using a rotary knob drivers had significantly less fixations on the touchscreen but those fixations lasted significantly longer. Difficulty of the driving task had no effect on the number of glances. When presenting information, the first glance is directed to the display the information appeared in. Using only sound and no visual information, the first glance is directed mostly to the center display rather than the cluster display. These findings should be considered for future design of IVIS and can help develop a more natural user interface.

This paper presents an advanced human-computer interaction system which supports the design of 3D model and makes 3D prototypes by merging technologies such as augmented reality (AR), hand gesture recognition, and 3D printing. This proposed development provides a system to enhance the user’s experience in designing of 3D model (3D prototypes). Beginners or novice designers can design 3D model intuitively. The proposed system provides an ability of manipulating with 3D model in 3D space such as translating, rotating, and scaling. Leap Motion was used to detect and recognize the hand gesture using the skeleton-based algorithm. This device sends the data of hand positions and gesture commands to display the virtual hands on the Microsoft HoloLens. The graphic manager manages the registration between the coordinate frame of Leap Motion and Microsoft HoloLens’ frame. The gesture-based modeling technique allows the user to design and manipulates 3D holographic objects. In addition, the HoloLens application is used to visualize holograms in the real environment’s scale. The designed holographic objects can be assembled, disassembled, interacted with the real environment surface. The holographic objects can be exported into the CAD file format from the mesh rendering to the ASCII STL structure which can be printed by a 3D printer automatically. In the experiment, the holographic objects can be modeled relatively to the physical objects. The system has been tested by eight participants. The purpose of this experiment was to explore the intuitive interaction techniques which facilitated in the designing and validated the relation between physical objects and holographic object. The output of the experiment was the real 3D printed prototype obtained from the designed holographics. The results of the system performance covered the operations such as translation, rotation, and scaling of holographic objects with respective to the actual object, the averaged time of designing, the precision of hand gesture interaction, and the usability.

Presently for various reasons people are concerned about directly touching the biometric scanners, therefore touch-less and non-invasive approach seems to be useful in practical applications. For the importance and complexity of handwritten character input in human-computer interaction system, a touch-less character input method has been proposed. A person uses his Finger Gesture Movement spot for writing in the air in this method, the video of Finger Gesture movement in air is recorded by a camera and processed utilizing computer vision technology, then the handwritten character image is reconstructed, finally, the reconstructed character is recognized. The algorithm of Finger Gesture spot detection and character image recovery is given, and their effectively has been verified experimentally in this paper. Depending on the hand motion dynamics, treated as a bio-metrics; as an input pattern for recognition system, finger Gesture movement can be a sufficient base for efficient user identification.

Most recent smartphones are controlled by touch screens, creating a need for hands-free input techniques. Voice is a simple means of input. However, this can be stressful in public spaces, and the recognition rate is low in noisy backgrounds. We propose a touch-free input technique using lip shapes. Vowels are detected by lip shape and used as commands. This creates a touch-free operation (like voice input) without actually requiring voice. We explored the recognition accuracies of each vowel of the Japanese moras. Vowels were identified with high accuracy by means of the characteristic lip shape.

Activity recognition is useful in applications for daily life, including automatic patient monitoring and working-state analysis. Even though some studies have developed methods to recognize daily activities, misclassification has been found to occur frequently for activities that involve small hand movements. This paper evaluates a method that uses acceleration data from both wrists and machine learning classifiers to recognize deskwork activities with small hand movements. The acceleration data are measured using sensors attached on both of the user’s wrists. The maximum, minimum, average, and Fourier transform coefficients of the segmented time series are extracted as features from the measured acceleration data. Combination of two types of features were evaluated to classify four deskwork activities with the support vector machine (SVM) and random forest algorithms. SVMs with the basic statistical feature vectors of both hands achieved the highest recognition accuracy, i.e., an accuracy of 0.94 for all participants. The results revealed that the acceleration data from both wrists can effectively recognize deskwork activities.

This paper outlines the use of an orientation correction algorithm for a miniature commercial-grade Inertial Measurement Unit to improve orientation tracking of human hand motion and also to improve 3D User Interfaces experience to become more realistic. The algorithm uses the combination of gyroscope, accelerometer and magnetometer measurements to eliminate the drift in orientation measurement which is caused by the accumulation of the bias offset error in the gyroscope readings. The algorithm consists of three parts, which are: (1) bias offset estimation, (2) quaternion correction using gravity vector and magnetic North vector, and (3) quaternion interpolation. The bias offset estimation is performed during periods when the sensor is estimated to be static, when the gyroscope reading would provide only the bias offset error for prediction. The quaternion was calculated based on unbiased angular velocity and then used to rotate the gravity vector and magnetic North vector in the Earth’s frame resulting in the calculated gravity vector and magnetic North vector in the sensor’s frame. The angular errors between calculated and measured gravity vector and the angle between calculated and measured magnetic North vector are used to calculate the correction quaternion that must be applied to the previous quaternion result. The result of the orientation estimation using this algorithm can be used to track the orientation of human hand motion with less drift and improved orientation accuracy than achieved with the on-board Kalman-based orientation filtering.

Contactless integrated circuit (IC) cards, such as employee ID and prepaid cards, are widely used. However, the contactless IC card is only used for ‘hold over’ operations. Here, we develop AccelTag, a contactless IC card equipped with an acceleration sensor and a liquid crystal display (LCD); we thus extend the functionality of contactless IC cards. AccelTag employs high-function radiofrequency identification (RFID) technology, driving the acceleration sensor and the LCD without a battery. AccelTag supports gestural operations such as slide and flip, and also accepts orientation as an input. We created a prototype of AccelTag and investigated its electrical characteristics and gesture recognition accuracy. The results showed that AccelTag can be used in the range of 3 cm to 15 cm from the reader and that the accuracy of recognizing the slide and flip gesture, and sensing card orientation was 65.8%, 99.2%, and 83.4% accuracy on average, respectively.

Dancing is a way of communication using the body and self-expression and is a kind of action where each individual’s uniqueness connects directly to his or her movements. Furthermore, how well a dancer can express his or her personality is one of the indicators of their ability, which proves the importance of personality in dancing. This study focused on personality in dancing, in particular the possibility of its extraction. Specifically, we asked skilled dancers and unskilled dancers to practice and perform a dance during which we acquired each individual’s bone structural data with the use of a Kinect sensor. Afterwards, we played back the data to each participant and asked them to choose what they thought were their own dancing forms, the form they most preferred, and the forms they thought were good. As a result, both the skilled and unskilled participants were capable of distinguishing their own dancing forms, which indicated the existence of a dancing personality. Furthermore, while there were differences between the skilled dancers and the unskilled ones, there was a common tendency of matching dance forms that participants favored and dance forms that participants considered good.

In designing and developing adaptive learning systems, it is desirable to incorporate as much information about the learner as possible to better tailor in instructional experience. Behavioral markers exhibited by the learner offer a source of information with the potential to shape instructional content. In the case of computer-based training environments, this source of information may include behaviors ranging from mouse cursor movement, key stroke dynamics, or eye tracking. We present methods for analyzing the mouse behavior of a learner using kinematic data in situations where knowledge of areas of interest on the screen are not known by the system a priori, as well as in multiple-choice scenarios to analyze the amount of attention spent by the user on various response items. The outcome of this work is to help inform and to influence future studies in adaptive learning which may seek to incorporate such sources of learner information.

Gesture is an important means of nonverbal communication and used in conveying messages before the advent of language. With the development of computer technology, gesture interaction has become a trend of natural and harmonious human-computer interaction. Accurate and efficient hand gesture recognition is the key to gesture interaction, not only in the interaction between human and electronic devices, but also in the interaction among users in virtual reality systems. Efficient gesture recognition demands users devote more attention to what gestures express, instead of features unrelated to gesture meaning. Therefore, the present study explored whether the processing of gesture orientation and the left/right hand information, the gesture features unrelated to gesture meaning, can be modulated by static and dynamic presentation in human’s recognition of manipulation gestures. The results showed that gesture orientation can be processed in recognition of static gestures of function-based manipulation (for example, hold a lighter and press a switch with thumb), but not dynamic gestures. However, gesture orientation can be processed in the recognition of dynamic gestures of structure-based manipulation (for example, pick up the lighter with your thumb and forefinger), the left/right hand information can be processed in the recognition of static gestures. It indicated that static and dynamic gesture presentation affected the recognition of manipulation gestures, and had different influence on structure- and function-based manipulation gestures. It suggested that dynamic function-based manipulation gestures were better options in human computer interaction, and the information unrelated to the meaning of gestures should be taken into consideration when presenting structure-based manipulation gestures, in order to ensure the successful gesture recognition. The findings provide theoretical guidance for the design of gesture interaction methods.

Gaze direction is one of the most important interaction cues that is widely used in human-machine interactions. In scenarios where participants’ head movement is involved and/or participants are sensitive to body-attached sensors, traditional gaze tracking methods, such as using commercial eye trackers are not appropriate. This is because the participants need to hold head pose during tracking or wear invasive sensors that are distractive and uncomfortable. Thus, head orientation has been used to approximate gaze directions in these cases. However, the difference between head orientation and gaze direction has not been thoroughly and numerically evaluated, and thus how to derive gaze direction accurately from head orientation is still an open question. In this article, we have two contributions in solving these problems. First, we evaluated the difference between people’s frontal head orientation and their gaze direction when looking at an object in different directions. Second, we developed functions that can map people’s gaze direction using their frontal head orientation. The accuracy of the proposed gaze tracking method is around 7°, and the method can be easily embedded on top of any existing remote head orientation method to perform non-invasive gaze direction estimation.

A user study was performed to compare three input methods (tilt, eye-tracking, head-tracking) with two gain levels (low, high) on a custom-made TrackMaze mobile game. The task involved maneuvering a virtual ball through a maze while trying to avoid walls. The game was developed in Swift using the ARKit framework. The TrueDepth front-facing camera of an Apple iPhone X was used for the eye-tracking and head-tracking conditions. We evaluated user performance (maze completion time, number of wall hits) and qualitative measures (ease of use, enjoyment, fatigue). Tilt input showed the best performance and eye-tracking showed the worst performance. The mean maze completion time was 12.3 s for tilt, 22.5 s for head-tracking, and 31.8 s for eye-tracking. High gain was 26% faster than low gain. Tilt was the most precise input method with only 1.06 wall hits per trial, compared to head-tracking (2.30) and eye-tracking (4.00). Participants preferred tilt and head-tracking over eye-tracking and noted that the eye-tracking interface was fatiguing and hard to use.

In the field of Gamification, much work has been devoted to designing gamified software using game design elements. However, there is presently insufficient research on designing gamified software investigating both entertainment and utilitarian elements [1]. Also, there are many ambiguous uses of this technology and technical difficulties, because of the limited documentation of Gamification data usage in the industry [2]. This study is inspired by the revised lexical approach [3] to investigate Gamification framework by analyzing large-scale online SMAs’ reviews. It includes the following major steps: (1) Collecting and downloading a large body of online reviews; (2) Employing Basic Natural Language Processing techniques to build a dictionary of Gamification descriptive adjectives; (3) Extracting users ratings of adjectives; (4) Conducting factor analyses to identify Gamification traits based on adjectives; (5) Conducting card sorting technique to further simplify the complex factor structure discovered in the factor analysis. This study demonstrates a new perspective to conduct research in the intersection of Game Studies and HCI (entertainment and utilitarian aspects). Gamification traits are identified for creating design guidelines and evaluating Gamification.

This research aims to explore the impact of cooperative or competitive gaming modes on players’ emotion and behaviors. We conducted a with-in subject study with 30 participants. Participants were asked to play a fighting game with a male research confederate in two different gameplay modes. We examined (1) self-reported preference, (2) changes in the gamers’ emotional states, (3) facial expression data captured by emotion recognition software, and (4) video recordings of the gaming sessions. The statistical results showed no significant differences. However, we were able to identify unique behavioral patterns shown in the competitive gameplay mode.

Virtual humans emerged as a topic of research in HCI and they have been used for various purposes. This paper explores the behavior of chess players in a virtual chess environment to gain more understanding about chess personalities. In particular, the focus of this research is investigating attack and defense strategies used by virtual chess grandmasters against different virtual class-B personalities who vary in their strength in the different stages of a game. These attack and defense strategies have attracted much attention in the chess community and are considered among the main aspects to chess players. They occur in different phases of the game: opening, middle game and endgame. The researcher examines virtual chess players to understand the psychology of competition between two grandmasters (attacker, defender) and three class-B chess players with different personalities: (a) strong at openings; (b) weak at openings, but strong at endgames and (c) balanced player. The virtual humans in this research represent personalities of real players. The empirical players’ results showed that the personalities could influence the error and the number of moves of the game for both grandmasters and class-B players. Such findings can be used in designing virtual chess players.

Design researchers should pay attention on the issue of gamification design, search for proper interdisciplinary theories and knowledge with explanations, deepen the understanding and application of the operation mechanism, and master the meaning and value of effective communication efficiency. The objectives of this study are summarized as below. 1. To apply gamification design to facilitate website design communication efficiency and user experiences. 2. To construct the web experiment to explore the impacts of gamification in the communication efficiency of websites. 3. To propose effective design principles applying gamification design to websites based on the test results of the web experiment. The research methods are further explained as following. Step 1: Construct experimented webs of control web and experimental web. Step 2: Test experimented webs and recruit users to participate and complete tasks on such two webs. Step 3: Questionnaire survey is preceded on users and semi-structured interviews aim to find out users’ web experience and perception by evaluating following dimensions. Ease of use, efficiency, comprehension, pleasure, satisfaction, and attraction motivation. Step 4: Discuss and analyze the effect of the use of gamification on the communication efficiency of web design, according to above test results, questionnaire, and interviews. Step 5: Conclude the principle of applying gamification to web design to enhance effective communication. It is expected that this study would contribute to designers and businesses understanding how to construct effective gamification design, offer users with better experiences, propose effective design principles for applying gamification design to websites, construct new interdisciplinary knowledge for design research, as well as create new opportunities of experience design for different industries and social and psychological needs.

We2 present an overview of current research in the measurement of enjoyment in video games. We attempt to systematize the disparate approaches found with the vocabulary and constructs of quasi-experimentation. In each area, we try to make some recommendations for improvement, and find some areas in need of further research.

As information technologies advance, our living environment is rapidly changes. However, support and consideration for animals as pets living with people is hardly done. Thus, pets are largely left behind with the changes in human living environments and its environments typically are designed just for people. For instance, when a cat walks on a keyboard and performs “cat typing” when its owner is trying to work, the cat is actually attracted to the motion and the sounds. Unfortunately, the owner is forced to keep the cat at a distance to comfortably use the computer. In this study, we develop an interactive tablet-based cat entertainment system that cats can enjoy near the owners, who otherwise need to work on their own computers. During this study, we conducted an experiment with several cats to investigate the effectiveness of our system, called CATouch!. As a result, the three phenomena clarified in this experiment are not facts but were identified as hypotheses. Results indicated a positive correlation between cat entertainment and having access to their own equipment.

The evolution of mobility sector towards a multimodal and multi-service approach enables new possibilities of interaction for travellers. At once it creates a complex ecosystem where the final users are one of the main key components for the effectiveness and the success of the deployed mobility strategies and solutions. It implies that, both for academic and commercial purposes, a remarkable attention should be put on the design approaches focusing on human aspects in interactive systems. Moreover different methods aiming at enhancing the user experience should be exploited, in order to trigger desirable and worthy innovations. So in this paper we focus on gamification for improving the quality of interaction with the mobility services. In effect, mobility represents a more and more promising domain for the application of playful solutions, although in this field it is nowadays employed mostly for incentivizing smart and sustainable behaviours, also in combination with crowdsourcing. However we can suppose a wider use of this approach in the mobility services, e.g. to improve the overall traveller experience and to increase an active collaboration among the stakeholders. In detail, in this paper we will discuss three main variables to identify which possibilities can emerge in future mobility services by applying a gamification approach: the different stages of a journey, for better knowing the contexts of action and the needs of people potentially interested in; the devices to be exploited, for better accomplishing gamification purposes; the game components, for better understanding how they contribute to fulfill the traveller objectives.

With the increasing popularity of online games, more and more studies have been undertaken to identify key factors impacting users’ acceptance of online games. However, even game designers noticed most of these key factors long time ago, the average life cycle of a game is still very low. This study is trying to research the online game from game developers’ perspectives. One of the main strategies to extend the game life cycle is to stimulate game players’ impulse purchase in the game. This study evaluate the effects of temptation on game players’ unplanned purchases. We propose that temptations in the online games associated with players’ flow experiences, and further influence their intentions of impulse purchases.