Interface Layout Research Articles

Enhancing User Experience on Social Media Platforms: A Flow Theory-Based Approach

In recent years, social media platforms, such as Facebook and Twitter have seen rapid growth and are favored by users of all ages. However, in the age of information overload, the quality of interactions on social media platforms varies significantly, leading to negative feelings among users and affecting their overall experience and loyalty. This study takes the Flow theory as its starting point and investigates the needs of social media users at various stages of the flow experience. We propose modifications to the flow theory model with the aim of enhancing user experience and satisfaction. Firstly, based on literature review, we identify micro-level issues of the product, propose hypotheses, and construct validation experiments in the context of social media. The experiment collects Electrodermal Activity (EDA) and heart rate variability (HRV) data of 31 participants using a multi-channel physiological instrument and collects their emotional experience data using the Pleasure-Arousal-Dominance (PAD) scale. Results indicate that a combined textual-graphical interface layout is superior to other layouts in positively inducing flow and emotional experiences. Positive content tonality is more effective at eliciting positive flow and emotional experiences than negative or neutral content. Video presentations have a stronger sense of immersion and emotional expression, making them more conducive to inducing flow experiences and positive emotional feedback. This study, grounded in user psychology, provides a theoretical framework based on flow and emotional experiences for social media product design, quantitatively examining the positive psychological activities of users when using social media.

User-Centered Design Strategies for Age-Friendly Mobile News Apps

With the increasing elderly population, catering to the digital news needs of the elderly has become increasingly crucial. This study employs factor analysis to explore the requirements and challenges of elderly individuals when using mobile news applications, aiming to provide strategies and directions for age-friendly design of mobile news applications. The research first summarizes a series of key factors that influence elderly users when using mobile news applications, categorizing them into three primary factors: usability and navigation, visual presentation and readability, and interaction and touch controls. Further entropy weight analysis reveals that the usability and navigation factor holds the highest priority for improvement, followed by visual presentation and readability, and lastly, interaction and touch controls. Based on these findings, we propose a series of age-friendly design strategies, including rational interface layout, clear text and images, and user-friendly interaction controls. These strategies not only enhance the digital news experience for elderly users but also offer valuable guidance and innovation for the field of mobile application design.

Research on Universal Design of Smart Home Interface Navigation Based on Visual Interaction

The study focuses on analyzing the design characteristics of display and control interface navigation in smart home terminals for users of different ages. By examining the design features of the current typical smart home terminal display and control interface navigation, interface navigation design is the research object. Experimental research is conducted with young adult group (n = 15) and middle-aged to elderly group (n = 15) participants to identify the optimal interface navigation design through specific behavioral indicators, eye movement indicators, and subjective indicators. The results show that different interface layouts impact task completion performance. Middle-aged and older individuals perform better with multi-level highlighting operations. Both age groups prefer interface layouts featuring less-level dual navigation, specifically the left-side type, and multi-level highlighting. These results can improve the versatility of smart home interface design, expand the user base, and provide information for developing smart products.

Human body features recognition based adaptive user interface for extra-large touch screens

With the widespread use of extra-large touch screens (eLTS) in various settings such as work and education, interaction efficiency and user experience have garnered increased attention. The current user interface (UI) layouts of eLTS are primarily categorized into two modes: fixed position and manual adjustment. The fixed UI layout fails to accommodate users of different heights and sizes, while the manual adjustment mode involves cumbersome steps and lacks sufficient flexibility. This study proposes an adaptive UI for eLTS. The optimal operational area on the eLTS is determined based on users’ height, eye level, arm length, face orientation, and distance from the screen. The eLTS menu is then positioned and displayed within this optimal area. Simulations involving users of various heights (P1 female, P50 male and female, and P99 male) were conducted to evaluate fatigue using the rapid upper limb assessment (RULA) method. The results indicate that the proposed adaptive UI significantly reduces user fatigue.

A Study of Key Factors Influencing the Usability of Smartphone Graphical User Interfaces for Older Adults

This study investigates the key factors influencing the usability of smartphone graphical user interfaces (GUIs) among elderly users in Shanxi Province, China. A total of 1,111 healthy individuals aged 60-75 years participated in the study. Quantitative analysis methods, including descriptive statistics, Pearson correlation, regression analysis, and mediation and moderation analysis, were employed to examine the interactions between user characteristics (age, education, experience, health status) and GUI design factors (interface layout, text and icon design, feedback mechanisms, information presentation) about usability metrics (cognitive load, interaction barriers, user experience). The analysis revealed that both user characteristics and GUI design factors significantly impact usability outcomes. Specifically, GUI design factors were found to mediate the relationship between user characteristics and usability, while user characteristics moderated the effects of GUI design on usability. These findings underscore the necessity of tailored interface design to enhance user experience and promote digital inclusion among elderly populations. Practical recommendations include the use of larger and more readable text, simplified iconography, and clear, immediate feedback to users. Such adjustments can significantly improve usability and foster greater digital inclusion. This research contributes valuable insights to both theoretical understanding and practical applications in the design of age-appropriate mobile interfaces.

Cognitive evaluation based on regression and eye-tracking for layout on human–computer multi-interface

ABSTRACT The human–computer cooperation process guided by natural interaction, intelligent interaction, and human–computer integration is gradually becoming a new trend in human–computer interaction. Cooperative scenarios of human–computer interaction systems often contain multi-interface and multi-device results in edges often interrupt the cognitive ergonomics of interface layout. This research takes typical areas as an example to establish a stepwise regression model to predict reaction time at an arbitrary position on the left interface. It uses a foveal region to position the starting point of attention and a parafoveal region to calculate the radius of each objective area, and design 10 similar tasks to analyze eye-tracking indexes through physiological assessment. Unlike fixed thinking such as spatial proximity on multi-interfaces, this research summarises cognitive features of layout based on the positive and negative effects of edge impact through eye-tracking analysis. It analyzes cognition including input, process, and output in human–computer cooperation from human intelligence and artificial intelligence respectively, and visualises the mapping relationship between these indexes and specific stages of cognition. Besides, the quantitative evaluation of the regression equation and qualitative analysis of the eye-tracking indexes provide a reference for other interfaces around the front interface.

Research on UI Interface Design of NAIS Small Program--Research on APP Design based on KANO Model

With the popularization of the mobile Internet and the wide application of smartphones, the importance of the UI interface design of the small program, as an important window for the interaction between the brand and the user, has become more and more prominent. This paper adopts the KANO model to analyze the UI interface of the NAIS applet deeply and puts forward targeted improvement suggestions. Through the KANO model to analyze the basic needs, expectation needs and excitement needs of the target users, this paper aims to match the young aesthetics and shape a unique interface style through the three aspects of design style and color matching, interface layout and function setting, interaction optimization and kinetic effect design; optimize the user experience and enhance the operation convenience; strengthen the brand identity and improve the competitiveness of the market.

Optimization of electrical control equipment interface layout with cognitive load based on pso algorithm

Abstract Addressing the complexity of current impregnation machine electrical control interfaces, this study proposes optimization methods for their layout design. It incorporates factors affecting cognitive load during interface interaction, formulating three principles: highlighting essential elements, operation sequence, and element relevance. These principles guide the construction of a mathematical model for the optimization of electrical equipment control interface layouts. The Particle Swarm Optimization algorithm is applied to solve the model’s objective function, producing optimized layouts, which are then validated through eye-tracking experiments. The results demonstrate the method’s effectiveness in optimizing control interface layouts, aligning with operators’ intuitive logic.

Utilizing Multiple Regression Analysis and Entropy Method for Automated Aesthetic Evaluation of Interface Layouts

Aesthetic evaluation of increasingly complex and personalized human–computer interaction interfaces serves as a critical bridge between humans and machines, fundamentally enhancing various interaction factors. This study addresses the challenges in aesthetic evaluation by adjusting existing methodologies to incorporate seven aesthetic metrics: density, symmetry, balance, proportionality, uniformity, simplicity, and sequence. These metrics were effectively integrated into a composite evaluation metric through both multiple regression analysis and entropy methods, with the efficacy of both fitting methods validated. Leveraging automatic segmentation and recognition technology for interface screenshots, this research enables rapid, automated acquisition of evaluations for the seven metrics and the composite index, leading to the development of a prototype system for interface layout aesthetic assessment. Aimed at reducing the time, manpower, and resources required for interface evaluation, this study enhances the universality, compatibility, and flexibility of layout assessments. It promotes integration at any stage of the design process, significantly benefiting lightweight rapid evaluation and iterative design cycles, thereby advancing the field of interface aesthetic evaluation.

The Effect of Touchscreen Layout Division on the Usability and Driving Safety of In-Vehicle Information Systems

Compared to traditional physical controls, in-vehicle touchscreen interaction relies more on vision. Irrational In-Vehicle Information System (IVIS) interface layout design can lead to decreased driver performance and even serious traffic accidents. This study investigated the impact of IVIS layouts on usability and driving safety. We extracted and analyzed the current mainstream IVIS homepage layouts in the market and summarized four different layout structures. An experiment was conducted on a driving simulator to examine the usability of the IVIS layout design based on task reaction time, error rate, NASA-TLX (a subjective workload assessment scale developed by NASA), and subjective preference (PREF). The safety issues of IVIS layout design were also examined based on standard deviation lane position (SDLP), speed variation (SV), mean glance time, mean number of glances, and blink frequency. This study recorded and evaluated the driving performance of 40 participants during real driving tasks at four speeds (0, 60, 90, and 120 km/h). Results showed that there were significant differences in task reaction time, NASA-TLX, PREF, mean glance time, SDLP, and SV among the four layouts. Furthermore, we observed that these four layouts had varying effects on usability and driving safety at four speeds. In the stationary state, the three-partition layouts were more efficient, while the two-partition layouts had more advantages during driving. Meanwhile, the horizontal dock bar layout interfaces have more advantages compared to the vertical dock bar interface. The study provides empirical evidence for optimizing the IVIS interface layout design for enhanced usability and driving safety.

Cognitive evaluation of HUD interface layout for intelligent automotive based on Bayesian BWM and Gray-TOPSIS

To reduce drivers’ cognitive load during the driving process, The present study concentrates on the cognitive evaluation and analysis of the Head-Up Display (HUD) interface layout, aiming to enhance human cognitive efficiency. Initially, a combination of eye-tracking technology and cognitive load theory is used to investigate users’ attention allocation and changes in eye movement indicators, followed by the conversion of these indicators. A comprehensive HUD interface layout evaluation system is established, considering structural layout esthetics, task efficiency, and cognitive load. To achieve this, an intelligent cognitive evaluation method for the automotive HUD interface layout is proposed, based on the Bayesian BWM and Gray-TOPSIS. Bayesian BWM is employed to determine the weights of evaluation indicators, followed by Gray-TOPSIS to assess and rank the layout candidate solutions. Experimental results indicate that in the optimal layout design, users exhibit fewer eye movements, shorter gaze durations, esthetically pleasing interface structures, and lower cognitive loads. Furthermore, comparative experiments validate the effectiveness and stability of the Bayesian BWM and Gray-TOPSIS methods. These findings offer guidance and reference for further optimizing the layout of intelligent automotive HUD interfaces.

Online education in design disciplines: factors influencing the interactive experience of group learning

There has been much previous research into online group learning, but they have not been aware of or focused on the challenges that design disciplines encounter in terms of interaction when moving to online delivery. This qualitative study comprised 3 participatory design workshops and 22 one-to-one interviews that included a total of 34 teachers and students from the School of Design at the University of Leeds. Participants reported the challenges and feelings they encountered in online group learning during the COVID-19 pandemic. The study found that the interactive experience of group learning is mainly influenced by the size of the group, the layout of the platform interface, the teacher’s management style and the conflict within the group, with more far-reaching discussions providing specific questions and subtle suggestions. The article’s findings can inform future strategies for online group learning for students and teachers of design disciplines in design higher education institutions.

Effect of interface layout design of a public library website on information-seeking experience for elderly people

PurposeTargeting the common functions of the Zhejiang Library website, elderly individuals were invited to complete six experimental tasks on the improved website interfaces, and subjective data (PAD emotion scale and usability evaluation) and objective data (eye movement data) were recorded to verify the effects of graphic layout and navigation position on the information-seeking experience of elderly individuals.Design/methodology/approachThis study analyzes the effect of the graphic layout and navigation position of the Zhejiang Library’s website interface on the emotional state, perceived usability and information-seeking time of elderly individuals, with the aim of providing guidance and suggestions for the elderly-oriented reform of the public library website.FindingsThe experimental results show that the graphic layout has a significant effect on the emotional state and perceived usability of elderly individuals, and the navigation position has a significant effect on the information-seeking time; the interaction between graphic layout and navigation position exerts a significant effect on the information-seeking time of elderly individuals. The eye movement data show that elderly individuals have a better information-seeking experience when the top navigation bar and image-text matched arrangement are used for the interface layout.Originality/valueThis study adopts a new approach combining subjective data and eye movement data to evaluate the effect of the public library website’s interface layout on the information-seeking experience for older people. The findings can provide a theoretical basis and methodological support for the elderly-oriented reform of public library websites. They can also provide scientific design suggestions for age-friendly interface layouts of other Internet products and service applications.

3D Motion Gesture Control : Gesture Recognition and Adaptation for Human Computer Interaction

Advancements in human-computer interaction (HCI) have paved the way for more intuitive and immersive interfaces. The first part of the paper delves into the fundamental principles of 3D gesture recognition, including sensor technologies, machine learning algorithms, and computer vision techniques. It discusses the challenges associated with accurate recognition in various environmental conditions and the ways in which these challenges are being addressed by researchers. The second part focuses on the adaptation aspect of the technology. It highlights how 3D gesture recognition can be integrated into adaptive HCI systems, enabling personalized and context-aware interactions. These adaptations can range from adjusting the interface layout to suit the user's preferences to dynamically changing the system's behavior based on the user's gestures. Additionally, the paper discusses the potential applications of 3D gesture recognition in fields such as gaming, virtual reality, healthcare, and beyond. It emphasizes the need for continued research to improve accuracy, robustness, and user-friendliness, ultimately driving the widespread adoption of 3D gesture recognition in HCI.

PalmSpace: Leveraging the palm for touchless interaction on public touch screen devices

Touchscreen is the primary solution to interact with public devices such as Automated Teller Machines (ATMs). However, the touch modality raises health concerns since users have to touch the screens, and therefore risking the spread of contagious diseases. We design PalmSpace, an alternate input technique leveraging users’ hand palms to interact with public devices. With Palmspace, UI elements are mapped onto the users’ palms and can be accessed by touching various locations directly on the palm. We conduct a series of user studies to evaluate several design options, such as interface layout, item size, preferred item location, and suitable feedback for items. Based on the results, we design PalmSpace and compare its performance with mid-air input. We show that PalmSpace is a potential solution to interact with public devices without using their touchscreen. We conclude with design guidelines for using the palm as an alternative input space for touchscreen devices.

Towards Inclusive Research and Resources in American Signed Languages

Creating high-quality resources that are easily accessible in American Sign Language (ASL) is important and valuable to the Deaf community. Simply adding videos to an English-centric user interface layout leads to unsatisfactory results because language conventions and differences in intuition create varying scanning patterns and expectations regarding the information's placement and presentation. Therefore, design choices regarding the videos and their surroundings must be made to overcome this challenge. In this work, we design interfaces that do not rely on English fluency. By promoting the widespread use and availability of well-designed ASL resources, we aim to support increased access and representation of ASL online materials for members of the Deaf community. We are developing an ASL-centric survey tool that would enable users to take surveys in ASL. Our objective is to study design elements that can help users navigate resources intuitively without relying on English. Lastly, we hope to contribute to cultivating access to collaborative human-centered methods and research by closely reflecting on HCI methods and moving towards creating a guideline to carry out research in ASL.

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Balanced Aesthetics: How Shape, Contrast, and Visual Force Affect Interface Layout

This study aims to investigate the effects of shape, contrast, and visual force on the visual weight of interface elements and provides corresponding experimental validations. The experiments employ representative abstract shapes as stimuli and conduct three visual weight experiments. The results of the shape experiment demonstrate significant effects of vertical and horizontal ellipses on visual weight, while polygons and rounded rectangles do not show significant effects. The contrast experiment reveals that increasing contrast significantly increases visual weight, particularly on a white background. The visual force experiment indicates that the direction of visual force influences visual weight, with a decrease in weight when directed towards the center of the interface and an increase when directed otherwise. Based on these experimental findings, we infer the underlying mechanisms of the effects of shape, contrast, and visual force on visual weight, providing empirical evidence for optimizing balance computational models.

The Shortest Route is Not Always the Fastest: Probability-Modeled Stereoscopic Eye Movement Completion Time in VR

Speed and consistency of target-shifting play a crucial role in human ability to perform complex tasks. Shifting our gaze between objects of interest quickly and consistently requires changes both in depth and direction. Gaze changes in depth are driven by slow, inconsistent vergence movements which rotate the eyes in opposite directions, while changes in direction are driven by ballistic, consistent movements called saccades , which rotate the eyes in the same direction. In the natural world, most of our eye movements are a combination of both types. While scientific consensus on the nature of saccades exists, vergence and combined movements remain less understood and agreed upon. We eschew the lack of scientific consensus in favor of proposing an operationalized computational model which predicts the completion time of any type of gaze movement during target-shifting in 3D. To this end, we conduct a psychophysical study in a stereo VR environment to collect more than 12,000 gaze movement trials, analyze the temporal distribution of the observed gaze movements, and fit a probabilistic model to the data. We perform a series of objective measurements and user studies to validate the model. The results demonstrate its predictive accuracy, generalization, as well as applications for optimizing visual performance by altering content placement. Lastly, we leverage the model to measure differences in human target-changing time relative to the natural world, as well as suggest scene-aware projection depth. By incorporating the complexities and randomness of human oculomotor control, we hope this research will support new behavior-aware metrics for VR/AR display design, interface layout, and gaze-contingent rendering.

Gaze Tracking for Hands-Free Human Using Deep Reinforcement Learning Approach

Abstract People with disabilities have new and advanced methods to communicate with the applications for virtual keyboards and other communication tools. In this paper, we utilized a novel deep reinforcement learning-based technique for determining the location of the accessible options for gaze-controlled tree-based menu selection system. A virtual English keyboard has been incorporated into the layout of the new user interface, which also includes improved requests for text modification through the gaze. The two methods used to manage the system are: 1) eye tracking for typing on the virtual keyboard and 2) eye tracking with a device for soft-switch utilizing deep reinforcement learning. Simulation results show that DRL based algorithm outperforms other baseline techniques in terms of total loss and accuracy.