This study analysed the effects of four parameters (current intensity, rising time, maintenance duration, and falling time) of ramped galvanic vestibular stimulation (GVS) on vestibular perception. Based on these findings, an optimal waveform for inducing roll sensation was designed and applied to a virtual reality (VR) flight simulator. Current intensity and rising time significantly affected perceived strength and annoyance, whereas maintenance duration affected only annoyance, and falling time showed no significant effects. Application of the recommended waveform in a VR flight simulator significantly increased presence and reduced simulator sickness compared with the no-GVS condition.

This study investigates how user satisfaction and output alignment evolve during iterative interactions with text-to-image generative AI across descriptive and creative tasks. 22 participants completed both task types while repeatedly modifying prompts. Descriptive tasks required replicating existing living spaces, while creative tasks involved designing imagined dream environments. We analyzed interaction satisfaction and image satisfaction across trials over the course of interaction, using regression and ANOVA. Based on regression analyses, we identified a “persistence paradox”: conducting more trials improved image satisfaction, but significantly decreased interaction satisfaction over time. Task type systematically shaped this pattern. ANOVA results showed that creative tasks yielded higher initial interaction satisfaction than descriptive tasks. Furthermore, overall output alignment was predicted by interaction satisfaction rather than objective image quality, underscoring that users judge success primarily through the process they experience. These findings highlight the need for text-to-image systems that actively manage frustration and expectations across tasks, supporting persistence without eroding user experience.

As home appliance interfaces become increasingly digitalized, users with visual impairment or spinal cord injury (SCI) face growing barriers to operating essential household devices. This study examines two prototype designs intended to improve accessibility: an acrylic panel with engraved grooves and Braille markings for washing machine touch panels, and a swing button that transforms pushing into a top-down pressing motion for microwave doors. Nine participants (five with visual impairment; four with SCI) evaluated the prototypes using a study-specific questionnaire combining Likert-scale and open-ended items. Both prototypes improved tactile guidance, reduced unintended activations, and enhanced usability within reachable ranges; an unexpected benefit was reduced glare for wheelchair users. However, tactile cues alone were insufficient for visually impaired users, who emphasized the need for voice feedback. These preliminary findings, though limited by sample size, support integrating accessibility into mainstream appliances rather than relegating it to specific products.

The emergence of large language models (LLMs) has expanded the potential of conversational AI in mental health support. Yet, counseling inherently relies on trust and relational qualities that may not transfer directly to LLM-based systems. We examine how users’ trust and experiences differ between LLM-based and human counseling and derive user-centered design implications. In a within-subjects study, 31 adults who recently experienced stress engaged in text-based sessions with both an LLM counselor and a human counselor. We assessed changes in subjective distress (SUDS), measured trust across five dimensions, and analyzed open-ended responses across trust levels for each counselor type. Overall, the human counselor condition received higher trust ratings, with the largest gaps in Faith and Personal Attachment, whereas Understandability was comparable across conditions. Open-ended feedback indicated that users’ experiences diverged in exploratory questioning, contextual understanding, emotional responsiveness, and personalization, motivating design considerations for LLM-based counseling systems.

In this study, we investigate usability issues in developing an expert network platform, providing valuable insights through agile testing and quantitative analysis compared to traditional expert qualitative methods. Simple usability tests conducted with college students revealed various problems related to User Experience (UX). Using Social Network Analysis (SNA), we identified 13 distinct clusters of issues. Through more detailed network analysis, we emphasized the importance of precise descriptions, consistent terminology, improved accessibility, and UI enhancements that increase reliability and professionalism of the service. By comparing the SNA results with expert qualitative analysis using the Affinity Diagram, this study demonstrates that simple, cost-effective testing can effectively identify usability issues and provide actionable insights. This approach allows small and medium-sized enterprises (SMEs) to enhance their platforms without extensive expert intervention. Future research should involve a more diverse range of user groups to refine these findings further and ensure that the platform adequately meets the needs of all potential users. By doing so, we aim to develop a more comprehensive understanding of the usability challenges.

We introduce an innovative exhibition program that generates personalized digital media art based on visitors' real-time emotions. In the exhibition, participants engage with the display by expressing various emotions with facial recognition artificial intelligence technology, triggering the creation of personalized artwork. We investigated whether incorporating the inner emotional states of each visitor, along with artificial intelligence technology, leads to more personalized and profound experiences. We compared our program to other tourism programs and observed significant differences in individuals' perceived realism, creativity, willingness to revisit, and preferences. The results demonstrate that visitors highly favored our program, eliciting a stronger sense of creativity and realism. Furthermore, it matched traditional outdoor activities in terms of individual preference and willingness to revisit. This study highlights the potential of combining psychology and technology to create captivating, personalized tourism experiences, suggesting that stakeholders adopt emotion-responsive digital programs to enhance visitor engagement and satisfaction.

Control devices are essential for interacting with displays in various fields. Therefore, effectively designing these controls and displays is crucial to ensure timely task completion and error avoidance. However, the complexity of these interactions has increased as the number of buttons on controllers has decreased while the amount of displayed information has grown. This study addresses usability issues caused by increased complexity. With familiar smart TV remote controls, we experimented with seven participants performing tasks using discrete and continuous controllers over 3 days. We measured task completion time (TCT) and user satisfaction to evaluate performance and learnability. Results showed that continuous controllers performed better for typing tasks, while discrete controllers excelled in content selection tasks. This study clarifies the interaction between tasks on displays and controllers by applying discrete and continuous concepts. Using commercially available remote controls in a familiar environment increases the generalizability of the findings. Further research in different domains and with dimension concepts can help address user discomfort with controllers that have fewer buttons but numerous functions.

This study presents a heuristic evaluation and analysis methodology to enhance online platform usability. Recognizing usability's critical role, especially in the information-rich online environment, the methodology employs expert evaluators using predefined heuristics for interface usability and information structure assessments. Twelve evaluators identified 71 usability issues on a patent-related matching service platform. Using Nielsen's heuristics and affinity diagrams, these issues were categorized into 13 groups. A quantitative evaluation framework was developed with Quality Function Deployment (QFD) matrix, linking customer requirements to usability improvements. The card sorting methodology restructured the website's menu and navigation system, resulting in a proposed sitemap redesign with a "Case Studies" menu and reorganized "Users" and "Experts" categories. The framework effectively identifies and prioritizes usability issues, providing a practical tool for small-scale enterprises. Future research should compare usability with competitors and develop decision-support systems to enhance user-centered design and website development.

Background The conventional Work Triangle principle has long been a guiding concept in kitchen design, aiming to optimize workflow and minimize workload. However, with the advent of modern appliances and evolving lifestyles, the effectiveness of the Work Triangle in addressing the diverse activities and needs of contemporary kitchens is increasingly limited.Objective This study aims to verify the validity of the Work Triangle in modern kitchen design and propose a kitchen modeling algorithm that facilitates customization based on layout and the area size from a user-centered perspective.Methods The research was conducted in two parts. In the first part, the validity of the Work Triangle was verified through the analysis of 38 actual apartment kitchen floor plans in Korea. Then the second part, a kitchen layout optimization model was developed using 0-1 integer programming to minimize the distance between kitchen appliances, incorporating the placement of modern appliances not included in the traditional Work Triangle.Results The statistical analysis of kitchen floor plans data showed that the impact of Work Triangle compliance on movement efficiency was limited, suggesting the need for customized kitchen design that reflects user behavior patterns and the placement of modern appliances and storage spaces. The model was evaluated through simulation, demonstrating its effectiveness in optimizing kitchen appliances layout.Conclusions The study emphasizes the need to consider actual usage patterns and the limitations of the Work Triangle in modern kitchen design, proposing a user-centered optimization model that enables customization based on individual cooking scenarios and lifestyles.

Managing vehicle stress and arousal is essential for safe and satisfying driving experiences. However, unexpected movements and degraded driving experience quality can cause rapid changes in arousal levels during driving. One of the important factors affecting the quality of the user experience is motion sickness. This study uses various biometric indicators to understand the impact of motion sickness severity and arousal levels. Specifically, this research investigates the relationship between biometric signals, particularly electrocardiogram (ECG) indicators, and motion sickness in real driving environments. By analyzing ECG-derived metrics, we aim to identify patterns associated with increased arousal and stress levels, potentially leading to the development of personalized driver support systems.

Motion sickness could significantly impact occupants’ experiences in vehicular environments, which has stimulated numerous studies investigating factors contributing to its severity in both human-driven and autonomous vehicles. This research aims to explore the primary themes of recent motion sickness studies and to identify the critical factors that are influenced by the type of engine and the driving entity. To this end, we have compiled research articles through a systematic literature review protocol, focusing on the past five years, which either carried out experimental investigations or mathematical simulations related to motion sickness. By applying network analysis to the keywords of these articles, we have identified the trends and thematic structure within the current body of research. Furthermore, we have assessed how these structures and trends differ according to the type of vehicle engine and driving entity. The results of this study are expected to provide insights and guidance for researchers researching motion sickness.

This study probes the influence of smartphone usage, backpack positioning, and varying neck angles on muscle activation, postural sway, and body discomfort during simulated public transportation. The experiment included 10 participants, aged mid-20 s to mid-30 s, with parameters including distinct neck angles and backpack positions (no backpack, front, and back). Findings reveal that the front backpack position generally caused the most significant postural sway and highest muscle activation, notably for the gastrocnemius (GN) muscle group and the overall muscle group statistic. Body discomfort surveys further indicated increased discomfort with the front backpack position, especially at a 45° neck angle. This research underscores the ergonomic implications of smartphone usage and backpack carriage during public transportation, which can guide future public health interventions and transit design strategies.

Motion sickness can occur in environments where new technologies, such as electric vehicles, are applied. Since motion sickness impedes user experience and the adoption of these technologies, accurate prediction is essential. This necessitates precise measurement of motion sickness variations across different environments to improve predictive model accuracy. However, current questionnaires lack detailed temporal and symptom-specific information, failing to provide accurate real-time data. To address this, we introduce the Real-Time Motion Sickness Scale (RMS), a practical tool designed for continuous monitoring of significant motion sickness symptoms. The RMS was developed by enhancing existing questionnaires through a systematic literature review and pilot tests. We validated its feasibility through a real-driving experiment with 24 passengers in an electric vehicle. The results demonstrated that the RMS accurately describes motion sickness severity and captures real-time changes in detail. Based on these findings, we discuss the applications of the RMS in motion sickness-provocative environments.

ObjectiveThis study investigated how user characteristics and driving context influence auditory experiences (AX) in electric vehicles (EVs), identifying distinct user types and their specific auditory needs and evaluation.BackgroundElectric vehicles (EVs) present unique opportunities for designing auditory experiences (AX) due to their quiet operation characteristics and acoustic vehicle alert systems (AVAS).MethodForty participants conducted real-driving experiments with an EV, experiencing sounds at low, medium, and high speeds. We applied systematic analysis combining topic modeling (BERTopic) and qualitative coding of think-aloud interviews and statistical analysis of questionnaire responses.ResultsFour user types were segmented by attitude (Dynamic vs. Conservative) and car type (EV vs. ICV owners). Text analysis revealed varying frequencies of concerns across user types regarding driving contexts, functional aspects, and affective aspects of AX. Statistical analysis showed significant differences among user types in sporty preferences and perceptions of affective properties (Sporty, Stylish, Comfort, and Calm). Driving contexts significantly influenced perceived Stylish and Calm characteristics.ConclusionThis study provides empirical evidence and design implications for customized AX in EVs design based on user characteristics and driving contexts.ApplicationThe findings can guide the development of personalized AX systems in EVs, enhancing both user satisfaction and safety through context-aware and user-centered design approaches.