Mirror Therapy (MT) effectively supports post-stroke upper-limb rehabilitation but requires professional supervision and often leads to low patient motivation. While digital MT systems address these limitations, they typically compromise the embodiment benefits of traditional mirrors. Through informant-driven design with interdisciplinary experts, we developed A-MIrror, an augmented reality mirror system that preserves the view of both mirrored hand and overlays digital guidance. Using dual cameras for eye and hand tracking, the system creates a visual illusion where both real and mirrored hands appear to naturally interact with virtual 3D objects on screen. Our evaluation with 14 post-stroke patients and 8 therapists demonstrates that A-MIrror significantly enhances motivation compared to traditional MT (p <.01) while achieving comparable embodiment experiences and even superior illusion latency (30.47% faster, p <.001) to traditional mirrors. This study presents a promising approach for independent post-stroke rehabilitation that integrates the strengths of both traditional and digital MT, offering insights for enhancing future digital rehabilitation applications.

This work investigates generative facial expression interfaces for intelligent agents from a meta-design perspective. We propose the Generative Personalized Facial Expression Interface (GPFEI) framework, which organizes rule-bounded spaces, character identity, and context–expression mapping to address challenges of control, coherence, and alignment in run-time facial expression generation. To operationalize this framework, we developed GenFaceUI, a proof-of-concept tool that enables designers to create templates, apply semantic tags, define rules, and iteratively test outcomes. We evaluated the tool through a qualitative study with twelve designers. The results show perceived gains in controllability and consistency, while revealing needs for structured visual mechanisms and lightweight explanations. These findings provide a conceptual framework, a proof-of-concept tool, and empirical insights that highlight both opportunities and challenges for advancing generative facial expression interfaces within a broader meta-design paradigm.

Parents with visual impairments (PVI) encounter unique challenges in engaging their sighted children in outdoor informal learning, yet little is known about how to address these barriers. We first conducted interviews with 11 mixed-ability families to uncover the perceptual, knowledge, and interactional challenges that limit parental participation. Building on these findings, we explored design opportunities across device form factors, interaction mechanisms, and modes of AI mediation through a design consultation, which led to the development of Bond, a distributed Wizard-of-Oz prototype. Bond combines a lightweight child-worn camera with parent-facing prompts to deliver timely, context-aware support for joint attention and conversation. A field study with 14 families demonstrated increased parental responsiveness, deepened parent–child dialogue, and strengthened parents’ confidence, while fostering children’s curiosity and co-exploration. We introduce Symbiotic Learning as a conceptual lens that reframes AI as a relational mediator bridging perceptual asymmetry, offering design considerations for inclusive, co-constructed learning in mixed-ability families.

Motion sickness, in addition to its persistent long-term effects, also exhibits short-term effects characterized as transient physiological discomfort, which changes rapidly with variations in locomotion. However, such discomforts are challenging to assess using current subjective scales and objective physiological measurements. To tackle this issue, this paper suggests continuous measurement methods designed specifically for evaluating transient physiological discomfort during VR locomotion. Through a user-elicitation study, three preferred measurement methods—’squeezing ball’, ’sliding thumb’, and ’rubbing thigh’—were identified. These techniques were then evaluated for reliability, validity, attention, presence, and workload, with ’sliding thumb’ identified as the most effective option. The paper expands traditional measurement methods to capture users’ physiological experiences in VR interactions, offering practical choices for researchers in this field along with an in-depth discussion of design considerations, detailed implementation guidelines, and potential ways to optimize the VR experiences utilizing the measurement data.

Chronic stress and anxiety severely affect breast cancer survivors’ (BCSs) mental health and well-being. Peer support has been shown to enhance psychological empowerment, while biofeedback offers a promising approach to improve physiological relaxation through self-regulation. However, few studies explored combining both for BCSs. We conducted a formative study with clinicians and BCSs to identify requirements and preferences for VR biofeedback. Informed by the findings, we proposed a VR-based dyadic biofeedback system, Cobreath, which integrates breathing and heart rate variability (HRV) feedback into a calming virtual environment, allowing two users to practice breathing-focused relaxation simultaneously. Through a clinical user study with ten clinicians and a between-subjects study with 32 BCSs, we demonstrated that Cobreath’s dyadic mode improved biofeedback effectiveness and provided a better user experience compared to the individual mode. We further discuss insights and design considerations for developing dyadic VR-biofeedback applications to support the mental well-being of BCSs and potential applications.