BuyMate: Making AI Interventions Effective in Promoting Rational Consumption in Live CommerceLive commerce platforms frequently employ algorithmic recommendations and time-limited promotions to trigger impulsive purchases, challenging rational consumer decision-making. While existing research has identified manipulative design patterns in live commerce, significant gaps remain in understanding consumer psychological motivations and developing counter-persuasion interventions. We conducted a multi-stage formative study involving surveys (N = 116), interviews (N = 21), and co-design workshops (N = 16) to explore user preferences for rational consumption support systems. Informed by these insights, we designed BuyMate, which provides gentle, real-time rational interventions through product comparison and persuasive speech reframing. A user evaluation (N = 35) demonstrates that the system effectively reduces impulsive purchases, enhances decision autonomy, and promotes sustainable consumption. This work contributes an AI-driven counter-persuasion approach, identifies user-centered principles for adaptive interventions, and offers practical guidance for responsible AI in digital commerce.2026SWShiyi Wang et al.Tsinghua universityAI-Assisted Decision-Making & AutomationAI Ethics, Fairness & AccountabilityRecommender System UXCHI
From Performers to Creators: Understanding Retired Women's Perceptions of Technology-Enhanced Dance PerformanceOver 100 million retired women in China engage in dance, but their performances are constrained by limited resources and age-related decline. While interactive dance technologies can enhance artistic expression, existing systems are largely inaccessible to non-professional older dancers. This paper explores how interactive dance technologies can be designed with an age-sensitive approach to support retired women in enhancing their stage performance. We conducted two workshops with community-based retired women dancers, employing interactive dance and LLM-powered video generation probes in co-design activities. Findings indicate that age-sensitive adaptations, such as low-barrier keyword input, motion-aligned visual effects, and participatory scaffolds, lowered technical barriers and fostered a sense of authorship. These features enabled retired women to empower their stage, transitioning from passive recipients of stage design to empowered co-creators of performance. We outline design implications for incorporating interactive dance and artificial intelligence-generated content (AIGC) into the cultural practices of retired women, offering broader strategies for age-sensitive creative technologies.2026DZDanlin Zheng et al.The Hong Kong University of Science and Technology (Guangzhou)Dance & Body Movement ComputingAffective Feedback & Emotion Regulation InterfacesCreative Collaboration & Feedback SystemsCHI
GatheringSense: AI-Generated Imagery and Embodied Experiences for Understanding Literati GatheringsChinese literati gatherings (Wenren Yaji), as a situated form of Chinese traditional culture, remain underexplored in depth. Although generative AI supports powerful multimodal generation, current cultural applications largely emphasize aesthetic reproduction and struggle to convey the deeper meanings of cultural rituals and social frameworks. Based on embodied cognition, we propose an AI-driven dual-path framework for cultural understanding, which we instantiate through GatheringSense, a literati-gathering experience. We conduct a mixed-methods study (N = 48) to compare how AI-generated multimodal content and embodied participation complement each other in supporting the understanding of literati gatherings and fostering cultural resonance. Our results show that AI-generated content effectively improves the readability of cultural symbols and initial emotional attraction, yet limitations in physical coherence and micro-level credibility may affect users’ satisfaction. In contrast, embodied experience significantly deepens participants’ understanding of ritual rules and social roles, and increases their psychological closeness and presence. Based on these findings, we offer empirical evidence and five transferable design implications for generative experience in cultural heritage.2026YZYou Zhou et al.The Hong Kong University of Science and Technology(Guangzhou))Generative AI (Text, Image, Music, Video)Digital Art Installations & Interactive PerformanceMuseum & Cultural Heritage DigitizationCHI
FIP: Endowing Robust Motion Capture on Daily Garment by Fusing Flex and Inertial SensorsWhat if our clothes could capture our body motion accurately? This paper introduces Flexible Inertial Poser (FIP), a novel motion-capturing system using daily garments with two elbow-attached flex sensors and four Inertial Measurement Units (IMUs). To address the inevitable sensor displacements in loose wearables which degrade joint tracking accuracy significantly, we identify the distinct characteristics of the flex and inertial sensor displacements and develop a Displacement Latent Diffusion Model and a Physics-informed Calibrator to compensate for sensor displacements based on such observations, resulting in a substantial improvement in motion capture accuracy. We also introduce a Pose Fusion Predictor to enhance multimodal sensor fusion. Extensive experiments demonstrate that our method achieves robust performance across varying body shapes and motions, significantly outperforming SOTA IMU approaches with a 19.5% improvement in angular error, a 26.4% improvement in elbow angular error, and a 30.1% improvement in positional error. FIP opens up opportunities for ubiquitous human-computer interactions and diverse interactive applications such as Metaverse, rehabilitation, and fitness analysis. Our project page can be seen at https://fangjw-0722.github.io/FIP.github.io/2025RZRuonan Zheng et al.Xiamen UniversityHaptic WearablesHuman Pose & Activity RecognitionCHI
CrowdBot: An Open-Environment Robot Management System for On-Campus ServicesWang 等人设计 CrowdBot 开放环境机器人管理系统，实现校园场景下机器人的自主导航与任务调度，为校园服务机器人的高效管理提供解决方案。2024YWYufei Wang et al.Domestic RobotsSocial Robot InteractionUbiComp
TouchEditor: Interaction Design and Evaluation of a Flexible Touchpad for Text Editing of Head-Mounted Displays in Speech-unfriendly EnvironmentsZhan 等人设计 TouchEditor 柔性触控板，解决语音不友好环境下头显显示器的文本编辑交互问题。2024LZLishuang Zhan et al.Head-Up Display (HUD) & Advanced Driver Assistance Systems (ADAS)Hand Gesture RecognitionVoice User Interface (VUI) DesignUbiComp
CrowdQ: Predicting the Queue State of Hospital Emergency Department Using Crowdsensing Mobility Data-Driven Models"Hospital Emergency Departments (EDs) are essential for providing emergency medical services, yet often overwhelmed due to increasing healthcare demand. Current methods for monitoring ED queue states, such as manual monitoring, video surveillance, and front-desk registration are inefficient, invasive, and delayed to provide real-time updates. To address these challenges, this paper proposes a novel framework, CrowdQ, which harnesses spatiotemporal crowdsensing data for real-time ED demand sensing, queue state modeling, and prediction. By utilizing vehicle trajectory and urban geographic environment data, CrowdQ can accurately estimate emergency visits from noisy traffic flows. Furthermore, it employs queueing theory to model the complex emergency service process with medical service data, effectively considering spatiotemporal dependencies and event context impact on ED queue states. Experiments conducted on large-scale crowdsensing urban traffic datasets and hospital information system datasets from Xiamen City demonstrate the framework's effectiveness. It achieves an F1 score of 0.93 in ED demand identification, effectively models the ED queue state of key hospitals, and reduces the error in queue state prediction by 18.5%-71.3% compared to baseline methods. CrowdQ, therefore, offers valuable alternatives for public emergency treatment information disclosure and maximized medical resource allocation." https://doi.org/10.1145/36108752023TSTieqi Shou et al.Content Moderation & Platform GovernancePublic Transit & Trip PlanningUbiComp
UQRCom: Underwater Wireless Communication Based on QR Code"While communication in the air has been a norm with the pervasiveness of WiFi and LTE infrastructure, underwater communication still faces a lot of challenges. Even nowadays, the main communication method for divers in underwater environment is hand gesture. There are multiple issues associated with gesture-based communication including limited amount of information and ambiguity. On the other hand, traditional RF-based wireless communication technologies which have achieved great success in the air can hardly work in underwater environment due to the extremely severe attenuation. In this paper, we propose UQRCom, an underwater wireless communication system designed for divers. We design a UQR code which stems from QR code and address the unique challenges in underwater environment such as color cast, contrast reduction and light interfere. With both real-world experiments and simulation, we show that the proposed system can achieve robust real-time communication in underwater environment. For UQR codes with a size of 19.8 cm x 19.8 cm, the communication distance can be 11.2 m and the achieved data rate (6.9 kbps ~ 13.6 kbps) is high enough for voice communication between divers. https://dl.acm.org/doi/10.1145/3571588"2023XLTieqi Shou et al.Ubiquitous ComputingUbiComp
A Data-Driven Context-Aware Health Inference System for Children during School Closures"Many countries have implemented school closures due to the outbreak of the COVID-19 pandemic, which has inevitably affected children's physical and mental health. It is vital for parents to pay special attention to their children's health status during school closures. However, it is difficult for parents to recognize the changes in their children's health, especially without visible symptoms, such as psychosocial functioning in mental health. Moreover, healthcare resources and understanding of the health and societal impact of COVID-19 are quite limited during the pandemic. Against this background, we collected real-world datasets from 1,172 children in Hong Kong during four time periods under different pandemic and school closure conditions from September 2019 to January 2022. Based on these data, we first perform exploratory data analysis to explore the impact of school closures on six health indicators, including physical activity intensity, physical functioning, self-rated health, psychosocial functioning, resilience, and connectedness. We further study the correlation between children's contextual characteristics (i.e., demographics, socioeconomic status, electronic device usage patterns, financial satisfaction, academic performance, sleep pattern, exercise habits, and dietary patterns) and the six health indicators. Subsequently, a health inference system is designed and developed to infer children's health status based on their contextual features to derive the risk factors of the six health indicators. The evaluation and case studies on real-world datasets show that this health inference system can help parents and authorities better understand key factors correlated with children's health status during school closures. https://doi.org/10.1145/3580800"2023ZJZhihan Jiang et al.Cognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Mental Health Apps & Online Support CommunitiesUbiComp
vMirror: Enhancing the Interaction with Occluded or Distant Objects in VR with Virtual MirrorsInteracting with out of reach or occluded VR objects can be cumbersome. Although users can change their position and orientation, such as via teleporting, to help observe and select, doing so frequently may cause loss of spatial orientation or motion sickness. We present vMirror, an interactive widget leveraging reflection of mirrors to observe and select distant or occluded objects. We first designed interaction techniques for placing mirrors and interacting with objects through mirrors. We then conducted a formative study to explore a semi-automated mirror placement method with manual adjustments. Next, we conducted a target-selection experiment to measure the effect of the mirror's orientation on users' performance. Results showed that vMirror can be as efficient as direct target selection for most mirror orientations. We further compared vMirror with teleport technique in a virtual treasure hunt game and measured participants’ task performance and subjective experiences. Finally, we discuss vMirorr user experience and present future directions.2021NLNianlong Li et al.Institute of Software, Chinese Academy of Sciences, Institute of Software, Chinese Academy of SciencesSocial & Collaborative VRImmersion & Presence ResearchCHI
Sensock: 3D Foot Reconstruction with Flexible SensorsCapturing 3D foot models is important for applications such as manufacturing customized shoes and creating clubfoot orthotics. In this paper, we propose a novel prototype, Sensock, to offer a fully wearable solution for the task of 3D foot reconstruction. The prototype consists of four soft stretchable sensors, made from silk fibroin yarn. We identify four characteristic foot girths based on the existing knowledge of foot anatomy, and measure their lengths with the resistance value of the stretchable sensors. A learning-based model is trained offline and maps the foot girths to the corresponding 3D foot shapes. We compare our method with existing solutions using red–green–blue (RGB) or RGBD (RGB-depth) cameras, and show the advantages of our method in terms of both efficiency and accuracy. In the user experiment, we find that the relative error of Sensock is lower than 0.55%. It performs consistently across different trials and is considered comfortable and suitable for long-term wearing.2020HZHechuan Zhang et al.Xiamen UniversityFull-Body Interaction & Embodied InputCircuit Making & Hardware PrototypingCustomizable & Personalized ObjectsCHI