Recovery is Relational: Digital Support Needs for Patients and Supporters in Eating Disorder RecoveryEating disorder (ED) recovery extends beyond therapy sessions, unfolding in vulnerable moments embedded in everyday life and relationships. Yet empirical understanding of how these moments arise, how supporters contribute, and how technologies might offer timely, contextual assistance remains limited. To address this…2026RCRyuhaerang Choi et al.Korea Advanced Institute of Science and TechnologyMental Health Apps & Online Support CommunitiesBehavior Change & Reflection TechnologySpecial Education TechnologyCHI
MIND: Empowering Mental Health Clinicians with Multimodal Data Insights through a Narrative DashboardAdvances in data collection enable the capture of rich patient-generated data: from passive sensing (e.g., wearables and smartphones) to active self-reports (e.g., cross-sectional surveys and ecological momentary assessments). Although prior research has demonstrated the utility of patient-generated data in mental hea…2026RZRuishi Zou et al.Columbia UniversityExplainable AI (XAI)AI-Assisted Decision-Making & AutomationMental Health Apps & Online Support CommunitiesCHI
SignGlass: First-Person View Comprehensive and Generalizable ASL Translation Using Wearable GlassCommunication barriers between Deaf and Hard-of-Hearing (DHH) individuals and hearing individuals remain a major challenge, highlighting the need for technologies that enable seamless sign language interpretation. However, current American Sign Language (ASL) recognition and translation systems face key limitations, i…2025YCYongxiang Cai et al.Binghamton UniversityElectrical Muscle Stimulation (EMS)Eye Tracking & Gaze InteractionCognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)UIST
The Odyssey Journey: Top-Tier Medical Resource Seeking for Specialized Disorder in ChinaIt is pivotal for patients to receive accurate health information, diagnoses, and timely treatments. However, in China, the significant imbalanced doctor-to-patient ratio intensifies the information and power asymmetries in doctor-patient relationships. Health information-seeking, which enables patients to collect inf…2025KCKa I Chan et al.Tsinghua UniversityChronic Disease Self-Management (Diabetes, Hypertension, etc.)Telemedicine & Remote Patient MonitoringCHI
MedAI-SciTS: Enhancing Interdisciplinary Collaboration between AI Researchers and Medical ExpertsIntegrating AI in healthcare requires effective interdisciplinary collaboration, yet challenges like methodological differences, terminology barriers, and divergent objectives persist. To address the issues, we introduce MedAI-SciTS, a structured approach combining a theoretical framework and a toolkit to improve coll…2025CCChen Cao et al.University of SheffieldEV Charging & Eco-Driving InterfacesHand Gesture RecognitionKnowledge Worker Tools & WorkflowsCHI
What Social Media Use Do People Regret? An Analysis of 34K Smartphone Screenshots with Multimodal LLMSmartphone users often regret aspects of their phone use, especially social media use. However, pinpointing specific ways in which the design of an interface contributes to regrettable use can be challenging due to the complexity of social media app features and user intentions. We conducted a one-week study with 17…2025LGLongjie Guo et al.University Of WashingtonExplainable AI (XAI)Social Platform Design & User BehaviorMisinformation & Fact-CheckingCHI
Promoting Prosociality via Micro-acts of Joy: A Large-Scale Well-Being Intervention StudyProsociality has been well-documented to positively impact mental, social, and physical well-being. However, existing studies of interventions for promoting prosociality have limitations such as small sample sizes or unclear benchmarks. To address this gap, we conducted a global-scale well-being intervention deployme…2025HGHitesh Goel et al.International Institute of Information TechnologyMental Health Apps & Online Support CommunitiesEmpowerment of Marginalized GroupsCHI
From Classification to Clinical Insights: Towards Analyzing and Reasoning About Mobile and Behavioral Health Data With Large Language ModelsEnglhardt 等人提出基于大语言模型的移动健康数据分析框架，实现从数据分类到临床洞察的推理转换。2024ZEZachary Englhardt et al.University Of WashingtonHuman Pose & Activity RecognitionHuman-LLM CollaborationUbiComp
AdaptiveVoice: Cognitively Adaptive Voice Interface for Driving AssistanceCurrent voice assistants present messages in a predefined format without considering users’ mental states. This paper presents an optimization-based approach to alleviate this issue which adjusts the level of details and speech speed of the voice messages according to the estimated cognitive load of the user. In th…2024SWShaoyue Wen et al.New York UniversityHead-Up Display (HUD) & Advanced Driver Assistance Systems (ADAS)Voice User Interface (VUI) DesignCHI
Fast-Forward Reality: Authoring Error-Free Context-Aware Policies with Real-Time Unit Tests in Extended RealityAdvances in ubiquitous computing have enabled end-user authoring of context-aware policies (CAPs) that control smart devices based on specific contexts of the user and environment. However, authoring CAPs accurately and avoiding run-time errors is challenging for end-users as it is difficult to foresee CAP behaviors u…2024XQXun Qian et al.Purdue UniversityContext-Aware ComputingUbiquitous ComputingCHI
InteractOut: Leveraging Interaction Proxies as Input Manipulation Strategies for Reducing Smartphone OveruseSmartphone overuse poses risks to people's physical and mental health. However, current intervention techniques mainly focus on explicitly changing screen content (i.e., output) and often fail to persistently reduce smartphone overuse due to being over-restrictive or over-flexible. We present the design and implementa…2024TLTao Lu et al.University of MichiganNotification & Interruption ManagementWorkplace Wellbeing & Work StressCHI
From Text to Self: Users’ Perception of AIMC Tools on Interpersonal Communication and SelfIn the rapidly evolving landscape of AI-mediated communication (AIMC), tools powered by Large Language Models (LLMs) are becoming integral to interpersonal communication. Employing a mixed-methods approach, we conducted a one-week diary and interview study to explore users’ perceptions of these tools’ ability to: 1) s…2024YFYue Fu et al.University Of WashingtonMultilingual & Cross-Cultural Voice InteractionHuman-LLM CollaborationExplainable AI (XAI)CHI
MindShift: Leveraging Large Language Models for Mental-States-Based Problematic Smartphone Use InterventionProblematic smartphone use negatively affects physical and mental health. Despite the wide range of prior research, existing persuasive techniques are not flexible enough to provide dynamic persuasion content based on users’ physical contexts and mental states. We first conducted a Wizard-of-Oz study (N=12) and an int…2024RWRuolan Wu et al.Tsinghua UniversityHuman-LLM CollaborationMental Health Apps & Online Support CommunitiesPrivacy by Design & User ControlCHI
Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse InterventionDespite a rich history of investigating smartphone overuse intervention techniques, AI-based just-in-time adaptive intervention (JITAI) methods for overuse reduction are lacking. We develop Time2Stop, an intelligent, adaptive, and explainable JITAI system that leverages machine learning to identify optimal interventio…2024AOAdiba Orzikulova et al.Korea Advanced Institute of Science and TechnologyExplainable AI (XAI)AI-Assisted Decision-Making & AutomationNotification & Interruption ManagementCHI
Auth+Track: Enabling Authentication Free Interaction on Smartphone by Continuous User TrackingIn this paper, we propose Auth+Track, a novel authentication model that aims to reduce redundant authentication in everyday smartphone usage. By sparse authentication and continuous tracking of user's status, Auth+Track eliminates the "gap" authentication between fragmented sessions and enables "Authentication Free wh…2021CLChen Liang et al.Tsinghua UniversityHuman Pose & Activity RecognitionPasswords & AuthenticationCHI