Yiqi Xiao

While light-based external human–machine interfaces (eHMIs) on automated vehicles (AVs) are increasingly studied to mediate pedestrian–vehicle conflicts, gaps persist in understanding how specific dynamic features of the AV’s headlights influence pedestrians’ prediction of its yielding intention and their crossing behavior. This study systematically investigates the effects of dynamic elements of vehicle lighting—including animation patterns, animation speed, and light-emitting area—on pedestrians’ objective and subjective evaluations. A factorial design framework was employed, where participants viewed video simulations of an approaching AV displaying headlight designs combining multiple dynamic features. For different vehicle motion states, the vehicle–pedestrian distance was integrated as a variable to examine its interaction effect with lighting features. Objective measures of cueing effects were complemented by subjective ratings and user preference study via questionnaires. Results showed that there were more crossing behaviors of the pedestrian when presenting higher animation speed of dynamic light eHMIs. Animation pattern and light-emitting area does not play an important role in pedestrian decision-making, but proper design of these two features can evoke higher visual attention. When the vehicle–pedestrian distance is longer, the dynamic features of lighting will more affect people’s willingness to cross. The effects of light eHMIs seemed more significant for the AV travelling in constant speed. Our findings advance preliminary suggestions for selecting light-based eHMIs in the appropriate scenarios and can contribute actionable insights for designing intuitive, human-centric AV–pedestrian negotiation strategies.

BACKGROUND Background: Over the past decade, wearable technology has garnered significant attention for its role in personal health management, particularly in activity monitoring and chronic disease management. These devices continuously collect physiological data, enabling users to track fitness and health metrics in real time. OBJECTIVE Objective: This review aimed to synthesize the current literature on the applications of wearable technology in activity monitoring, chronic disease management, and rehabilitation, and to explore future research directions and technological advancements. METHODS Methods: This review followed the PRISMA guidelines and conducted a systematic literature search across multiple databases, including PubMed, the Cochrane Library, IEEE Xplore, and Web of Science. Studies published between 2010 and 2025 were included, with a focus on wearable devices for health monitoring. Data extraction and quality assessment were performed using the Critical Appraisal Skills Programme (CASP) checklist. RESULTS Results: This review included 19 studies, focusing on the effectiveness of wearable devices in promoting physical activity, optimizing athletic performance, and supporting chronic disease management. Key findings include the potential of integrating multimodal sensors for real-time monitoring, AI-driven analytics for personalized health insights, and the role of wearable devices in rehabilitation. However, challenges remain, including data accuracy, user adherence, and privacy concerns. CONCLUSIONS Conclusion: Wearable technology demonstrates significant potential for enhancing health monitoring and exercise management. Future developments should address current limitations, including improving sensor accuracy, ensuring user comfort, and establishing standardized data protocols. With continued innovation, wearable devices are expected to become indispensable tools for proactive and personalized healthcare.

BACKGROUND Background: Cardiopulmonary resuscitation (CPR) is a critical skill for healthcare professionals, where the timeliness and precision of execution directly affect patient survival outcomes. Traditional CPR training methods often lack authentic haptic feedback, resulting in suboptimal skill transfer to real-world clinical scenarios. OBJECTIVE Objective: This study investigates how multimodal gamification can enhance CPR skill acquisition by integrating three distinct types of haptic feedback—vibrotactile, thermotactile, and electrotactile—into a serious game–based training system. The goal is to evaluate and compare the effectiveness of each feedback modality in supporting CPR training outcomes. METHODS Methods: We developed a serious game that provides real-time feedback on compression depth, frequency, and hand placement during training sessions. The system not only aids in guiding compression accuracy but also tracks the rate of target achievement. Three feedback modalities were individually assessed to determine their impact on improving CPR performance. RESULTS Results: Compared to conventional training methods, participants using the serious game demonstrated improved accuracy in compression depth and reported greater confidence in performing CPR. Performance improvements were observed with electrotactile, vibrotactile, and thermotactile feedback by 43.6%, 24.5%, and 17.7%, respectively. Among them, electrotactile feedback yielded the most significant performance gains, though System Usability Scale (SUS) ratings suggested a potential trade-off in user experience. CONCLUSIONS Conclusions: This work highlights the potential of serious games to bridge the gap between simulation-based training and real-life application, offering a novel approach for dynamic error correction and long-term skill retention through enhanced interactive experiences.

BACKGROUND Background: High-quality cardiopulmonary resuscitation (CPR) is critical for survival, but traditional training methods often fail to maintain learner engagement and ensure long-term skill retention. Serious games have emerged as a powerful strategy to address these challenges. However, their application remains under-explored in resource-limited, high-altitude regions like Tibet, where unique environmental and infrastructural barriers impede effective CPR education. OBJECTIVE Objective: This study developed and evaluated TibetCPR, a wearable serious game designed to teach and reinforce CPR skills under high-altitude conditions. Unlike conventional training systems, TibetCPR integrates gamified elements—including scoring, real-time feedback, and adaptive difficulty—to deliver an immersive learning experience tailored to local constraints. METHODS Methods: We designed a serious game built on three core pillars. First, a Narrative and Reward System immerses players in a rescue scenario where successful CPR compressions visually restore a patient's health from red to green. Each life saved contributes to a persistent "Life Tree," providing long-term motivation. Second, Real-time Feedback Mechanics use integrated audiovisual and electro-tactile cues to instantly guide player performance on compression rate and depth. Third, an Adaptive Difficulty Engine, powered by a hybrid CNN-LSTM model and a Q-learning algorithm, analyzes player performance to dynamically adjust feedback and personalize the challenge. The game's efficacy was evaluated in a quasi-experimental study (N=40), with player engagement assessed via the System Usability Scale (SUS) and qualitative feedback. RESULTS Results: After a 10-minute training session, participants using TibetCPR showed significantly greater improvement in compression accuracy and rhythm control compared to controls. The game’s score-driven progression, adaptive difficulty, and real-time multimodal feedback contributed to high engagement and effective learning, reflected in high System Usability Scale scores and positive user feedback. CONCLUSIONS Conclusions: TibetCPR demonstrates that a serious game-based approach, tailored for extreme environments and cultural contexts, can significantly improve CPR training outcomes. Its low cost and engaging design make it a promising tool for scalable, equitable emergency training in underserved regions.

The process of visual analytics is composed of the visual data exploration tasks supporting analytical reasoning. When performing analytical tasks with the interactive visual interfaces displayed by the large screen, physical discomforts such as gorilla-arm effect can be easily caused. To enrich the input space for analysts, there has been some researches concerning the cross-device analysis combining mobile devices with the large display. Although the effectiveness of expert-level designs has been demonstrated, little is known of the ordinary users’ preferences for using a mobile device to issue commands, especially the small one like smartwatch. We implement a three-stage study to investigate and validate these preferences. A total of 181 distinctive gestural inputs and 52 interface designs for 21 tasks were collected from analysts. Expert designers selected the best practices from these user-defined interactions. A performance test was subsequently developed to assess the selected interactions in terms of quantitative statistics and subjective ratings. Our work provides empirical support and proposes a set of design guidelines for optimizing watch-based interactions aimed at remote control of visual data on the large display. Through this research, we hope to advance the development of smartwatches as visual analytics tools and provide visual analysts with a better usage experience.

Social design produces strategic, systematic solutions or new cultures as a response to the complexity of social changes and, in consequence, designers who are used to the traditional way of ideation may not be well prepared for the requirements of social design. This paper identified the characteristics of the concept generation of industrial design students participating in a social design practice as novices. Using the think-aloud protocol, we collected the conversations and self-reports of students (n = 42). We then conducted a qualitative analysis of the designers’ activities with the inductive and deductive coding method. An effect of prior knowledge was found on the themes of concept, as well as on the concept generation strategies and modes that industrial designers would prefer. Through a factor analysis of the frequency of students’ design activities, six concept generation strategies were clustered. There were eight concept generation modes for social design we summarized with the journeys of designers' activities. This study also revealed the effect of concept generation strategies and modes of industrial design students on the quality of their social design concepts. The results may also shed light on the question how we can foster the quality of industrial designers to adapt to the extension of disciplinary boundary in design.

A stroke is the basic limb movement that both humans and animals naturally and repetitiously perform. Having been introduced into gestural interaction, mid-air stroke gestures saw a wide application range and quite intuitive use. In this paper, we present an approach for building command-to-gesture mapping that exploits the semantic association between interactive commands and the directions of mid-air unistroke gestures. Directional unistroke gestures make use of the symmetry of the semantics of commands, which makes a more systematic gesture set for users’ cognition and reduces the number of gestures users need to learn. However, the learnability of the directional unistroke gestures is varying with different commands. Through a user elicitation study, a gesture set containing eight directional mid-air unistroke gestures was selected by subjective ratings of the direction in respect to its association degree with the corresponding command. We evaluated this gesture set in a following study to investigate the learnability issue, and the directional mid-air unistroke gestures and user-preferred freehand gestures were compared. Our findings can offer preliminary evidence that “return”, “save”, “turn-off” and “mute” are the interaction commands more applicable to using directional mid-air unistrokes, which may have implication for the design of mid-air gestures in human–computer interaction.