Traditional ball sport training methods often lack targeted feedback and personalized guidance, limiting beginners’ ability to develop the rapid responses and precise movements essential for such sports. This study investigates the effectiveness of integrating Visual-Haptic Feedback into simulated ball sport training to enhance body awareness and coordination without increasing cognitive load. By delivering tactile feedback to the wrists and ankles, we aim to improve beginners’ motor skills and overall performance. Our research reviews advancements in human-computer interaction focused on enhancing bodily awareness and discusses the application of tactile feedback in sports training. Experimental results demonstrate that Visual-Haptic Feedback significantly enhances beginners’ body awareness, enabling them to perceive and adjust their movements more accurately without imposing a cognitive burden. Furthermore, this approach effectively standardizes and coordinates motor performance, with a particularly notable improvement in lower limb movements. Additionally, Visual-Haptic Feedback reduces the error rate in executing complex tasks and improves the precision of limb movements. This study enriches the understanding of using Visual-Haptic Feedback in sports training and highlights its potential to improve skills and body coordination, offering valuable insights for future applications and developments in this field.

Safe street crossing poses significant challenges for visually impaired pedestrians, who must rely on non-visual cues to assess crossing safety. Conventional assistive technologies often fail to provide real-time, actionable information about oncoming traffic, making independent navigation difficult, particularly in uncontrolled or vehicle-based crossing scenarios. To address these challenges, we designed and evaluated two assistive systems utilizing haptic and visual feedback, tailored for traffic signal-controlled intersections and vehicle-based crossings. The results indicate that visual feedback significantly improved decision efficiency at signalized intersections, enabling users to make faster decisions, regardless of their confidence levels. However, in vehicle-based crossings, where real-time hazard assessment is crucial, haptic feedback proved more effective, enhancing decision efficiency by enabling quicker and more intuitive judgments about approaching vehicles. Moreover, users generally preferred haptic feedback in both scenarios, citing its comfort and intuitiveness. These findings highlight the distinct challenges posed by different street-crossing environments and confirm the value of multimodal feedback systems in supporting visually impaired pedestrians. Our study provides important design insights for developing effective assistive technologies that enhance pedestrian safety and independence across varied urban settings.

Service robots (SRs) are increasingly deployed in commercial settings, yet the factors influencing their acceptance, particularly emotional design elements, remain understudied. This research investigates SR acceptance factors by integrating the technology acceptance model, the Computers Are Social Actors (CASA) framework, Kansei engineering (KE), and social presence theory (SPT) to examine how design elements influence user responses to SRs. Using structural equation modeling of survey data from 318 shoppers and hotel guests in China, we tested relationships between CASA attributes, emotional perceptions, social presence, and usage intention. The results revealed that communication style produced the strongest effects across all emotional dimensions, with cuteness and coolness directly influencing usage intention, while warmth and novelty operate through social presence mediation. Multi-group analysis identified significant gender differences in response patterns: male users prioritized communication-driven perceptions while female users responded more strongly to coolness attributes. These findings extend our understanding of acceptance factors in service robot adoption, highlighting the critical roles of emotional design, communication style, and gender differences, while suggesting differentiated design approaches for diverse user segments.

This study presents a systematic bibliometric review of wearable technologies aimed at vulnerable road user (VRU) safety, covering publications from 2000 to 2025. Guided by PRISMA procedures and a PICo-based search strategy, 58 records were extracted and analyzed in CiteSpace, yielding visualizations of collaboration networks, publication trajectories, and intellectual structures. The results indicate a clear evolution from single-purpose, stand-alone devices to integrated ecosystem solutions that address the needs of diverse VRU groups. Six dominant knowledge clusters emerged—street-crossing assistance, obstacle avoidance, human–computer interaction, cyclist safety, blind navigation, and smart glasses. Comparative analysis across pedestrians, cyclists and motorcyclists, and persons with disabilities shows three parallel transitions: single- to multisensory interfaces, reactive to predictive systems, and isolated devices to V2X-enabled ecosystems. Contemporary research emphasizes context-adaptive interfaces, seamless V2X integration, and user-centered design, and future work should focus on lightweight communication protocols, adaptive sensory algorithms, and personalized safety profiles. The review provides a consolidated knowledge map to inform researchers, practitioners, and policy-makers striving for inclusive and proactive road safety solutions.

Road safety for vulnerable road users, particularly cyclists, remains a critical global issue. This study explores the potential of multimodal visual and haptic interaction technologies to improve cyclists’ perception of and responsiveness to their surroundings. Through a systematic evaluation of various visual displays and Haptic Feedback mechanisms, this research aims to identify effective strategies for recognizing and localizing potential traffic hazards. Study 1 examines the design and effectiveness of Visual Feedback, focusing on factors such as feedback type, traffic scenarios, and target locations. Study 2 investigates the integration of Haptic Feedback through wearable vests to enhance cyclists’ awareness of peripheral vehicular activities. By conducting experiments in realistic traffic conditions, this research seeks to develop safety systems that are intuitive, cognitively efficient, and tailored to the needs of diverse user groups. This work advances multimodal interaction design for road safety and aims to contribute to a global reduction in traffic incidents involving vulnerable road users. The findings offer empirical insights for designing effective assistance systems for cyclists and other non-motorized vehicle users, thereby ensuring their safety within complex traffic environments.

Passengers often struggle to identify intended pickup locations when autonomous taxis (ATs) arrive, leading to confusion and delays. While prior external human–machine interface (eHMI) studies have focused on pedestrian crossings, few have systematically compared feedback modes and display positions for AT pickup guidance at varying distances. This study investigates the effectiveness of three eHMI feedback modes (Eye, Arrow, and Number) displayed at two positions (Body and Top) for communicating AT pickup locations. Through a controlled virtual reality experiment, we examined how these design variations impact user performance across key metrics including selection time, error rates, and decision confidence across varied parking distances. The results revealed distinct advantages for each feedback mode: Number feedback provided the fastest response times, particularly when displayed at the top position; Arrow feedback facilitated more confident decisions with lower error rates in close-range scenarios; and Eye feedback demonstrated superior performance in distant conditions by preventing severe identification errors. Body position displays consistently outperformed top-mounted ones, improving users’ understanding of the vehicle’s intended actions. These findings highlight the importance of context-aware eHMI systems that dynamically adapt to interaction distances and operational requirements. Based on our evidence, we propose practical design strategies for implementing these feedback modes in real-world AT services to optimize both system efficiency and user experience in urban mobility environments. Future work should address user learning challenges and validate these findings across diverse environmental conditions and implementation frameworks.