arXiv subjects

Mengyao Guo

Publications and source records attributed to Mengyao Guo.

8 recordsLinked to original sources

arXiv2025

ReHome Earth: A VR-Based Concept Validation for AI-Driven Space Homesickness Interventions

Space exploration has advanced rapidly, but the emotional needs of astronauts on long-duration missions remain underexplored. We present ReHome Earth, a dual-component design approach addressing space homesickness: 1) a future-oriented installation concept integrating transparent OLED displays with spaceship windows for real-time Earth connectivity, and 2) a functional VR prototype simulating astronaut isolation for testing AI-generated content effectiveness. Since accessing astronauts during missions is impossible, we conducted concept validation with terrestrial participants experiencing geographic displacement. Through evaluation with 84 proxy participants and 6 HCI experts, we demonstrate strong emotional resonance and validate three design implications: emotional pacing mechanisms, explainable biophysical feedback systems, and evolution from individual tools to collective affective infrastructure. Our contributions include a technically feasible space installation concept, a functional VR prototype for space HCI research, and empirical insights into the design of AI-driven emotional support systems for extreme isolation environments.

cs.HC↗

arXiv2025

Stories That Teach: Eastern Wisdom for Human-AI Creative Partnerships

This workshop explores innovative human-AI collaboration methodologies in HCI visual storytelling education through our established "gap-and-fill" approach. Drawing on Eastern aesthetic philosophies of intentional emptiness, including Chinese negative-space traditions, Japanese "ma" concepts, and contemporary design minimalism, we demonstrate how educators can teach students to maintain creative agency while strategically leveraging AI assistance. During this workshop, participants will experience a structured three-phase methodology: creating a human-led narrative foundation, identifying strategic gaps, and collaborating on AI enhancements. The workshop combines theoretical foundations with intensive hands-on practice, enabling participants to create compelling HCI visual narratives that demonstrate effective human-AI partnership. Through sequential art techniques, storyboarding exercises, and guided AI integration, attendees learn to communicate complex interactive concepts, accessibility solutions, and user experience flows while preserving narrative coherence and creative vision. Building on our successful workshops at ACM C&C 2025, this session specifically addresses the needs of the Chinese HCI community for culturally informed and pedagogically sound approaches to AI integration in creative education.

cs.HC↗

arXiv2025

I Prompt, it Generates, we Negotiate. Exploring Text-Image Intertextuality in Human-AI Co-Creation of Visual Narratives with VLMs

Creating meaningful visual narratives through human-AI collaboration requires understanding how text-image intertextuality emerges when textual intentions meet AI-generated visuals. We conducted a three-phase qualitative study with 15 participants using GPT-4o to investigate how novices navigate sequential visual narratives. Our findings show that users develop strategies to harness AI's semantic surplus by recognizing meaningful visual content beyond literal descriptions, iteratively refining prompts, and constructing narrative significance through complementary text-image relationships. We identified four distinct collaboration patterns and, through fsQCA's analysis, discovered three pathways to successful intertextual collaboration: Educational Collaborator, Technical Expert, and Visual Thinker. However, participants faced challenges, including cultural representation gaps, visual consistency issues, and difficulties translating narrative concepts into visual prompts. These findings contribute to HCI research by providing an empirical account of \textit{text-image intertextuality} in human-AI co-creation and proposing design implications for role-based AI assistants that better support iterative, human-led creative processes in visual storytelling.

cs.HC↗

arXiv2025

VR MRI Training for Adolescents: A Comparative Study of Gamified VR, Passive VR, 360° Video, and Traditional Educational Video

Meta Quest Store: https://www.meta.com/experiences/stanford-mri-simulator/8205539289482347/ Magnetic Resonance Imaging (MRI) can be a stressful experience for pediatric patients due to the loud acoustic environment, enclosed scanner bore, and a prolonged requirement to remain still. While sedation is commonly used to manage anxiety and motion, it carries clinical risks and logistical burdens. Traditional preparatory approaches, such as instructional videos and mock scans, often lack engagement for older children and adolescents. In this study, we present a comparative evaluation of four MRI preparation modalities: (1) a gamified virtual reality (VR) simulation that trains stillness through real-time feedback; (2) a passive VR experience replicating the MRI environment without interactivity; (3) a 360° first-person video of a real MRI procedure; and (4) a standard 2D educational video. Using a within-subjects design (N = 11, ages 10-16), we assess each method's impact on head motion data, anxiety reduction, procedural preparedness, usability, cognitive workload, and subjective preference. Results show that the gamified VR condition has significantly lower head motion (p < 0.001) and yielded the highest preparedness scores (p < 0.05). Head motion data were significantly correlated with learning outcomes (p < 0.01), suggesting that behavioral performance in VR strongly indicates procedural readiness. While all modalities reduced anxiety and were rated usable, interactive VR was preferred by most participants and demonstrated unique advantages in promoting engagement and behavioral rehearsal. We conclude with design recommendations for designing immersive simulations and integrating VR training into pediatric imaging workflows.

cs.HC↗

arXiv2025

Plant-Centric Metaverse: A Biocentric-Creation Framework for Ecological Art and Digital Symbiosis

Digital ecological art represents an emergent frontier where biological media converge with virtual environments. This study examines the paradigm shift from anthropocentric to plant-centered artistic narratives within the metaverse, contextualizing how digital platforms transform ecological expression. However, current frameworks fail to systematically guide artists in leveraging plant agency for digital symbiosis that transcends human-centered creation. We propose the Biocentric-Creation Transformation Ideology (BCTI) framework and validate it through multimodal case studies spanning bio-art, NFTs, and VR ecosystems (2013-2023). Our analysis reveals: (1) Metaverse ecosystems enable unprecedented plant-algorithm co-creation, with biological artworks increasing by 133% in premier archives (2020 vs 2013); (2) Digital symbiosis manifests through blockchain DAOs where plants govern human-plant collaborations; (3) Algorithmic photosynthesis in VR environments reshapes ecological aesthetics through real-time biodata translation. The BCTI framework advances ecological art theory by systematizing the transition from representation to plant-centered agency, offering artists a blueprint for post-anthropocene creation. This redefines environmental consciousness in virtual realms while establishing new protocols for cross-species digital collaboration.

cs.HC↗

arXiv2025

Human and Machine as Seen at the Co-Creation Age: A Co-Word Analysis in Human Machine Co-creation (2014-2024)

This paper explores the evolving landscape of human-machine co-creation, focusing on its development in the context of the ACM Conference on Human Factors in Computing Systems (CHI) from 2014 to 2024. We employ co-word analysis to identify emerging trends, central themes, and the intellectual trajectory of this field. The study highlights the shift from viewing machines as mere tools to recognizing them as collaborative partners in creative processes. By understanding these dynamics, we aim to provide insights into the implications of this paradigm shift for creativity, innovation, and societal impact, ultimately fostering a more inclusive and effective approach to human-machine interaction in various domains.

cs.HC↗

arXiv2025

CyanKitten: AI-Driven Markerless Motion Capture for Improved Elderly Well-Being

This paper introduces CyanKitten, an interactive virtual companion system tailored for elderly users, integrating advanced posture recognition, behavior recognition, and multimodal interaction capabilities. The system utilizes a three-tier architecture to process and interpret user movements and gestures, leveraging a dual-camera setup and a convolutional neural network trained explicitly on elderly movement patterns. The behavior recognition module identifies and responds to three key interactive gestures: greeting waves, petting motions, and heart-making gestures. A multimodal integration layer also combines visual and audio inputs to facilitate natural and intuitive interactions. This paper outlines the technical implementation of each component, addressing challenges such as elderly-specific movement characteristics, real-time processing demands, and environmental adaptability. The result is an engaging and accessible virtual interaction experience designed to enhance the quality of life for elderly users.

cs.HC↗

arXiv2023

Exploring the Intersection of Complex Aesthetics and Generative AI for Promoting Cultural Creativity in Rural China after the Post-Pandemic Era

This paper explores using generative AI and aesthetics to promote cultural creativity in rural China amidst COVID-19's impact. Through literature reviews, case studies, surveys, and text analysis, it examines art and technology applications in rural contexts and identifies key challenges. The study finds artworks often fail to resonate locally, while reliance on external artists limits sustainability. Hence, nurturing grassroots "artist villagers" through AI is proposed. Our approach involves training machine learning on subjective aesthetics to generate culturally relevant content. Interactive AI media can also boost tourism while preserving heritage. This pioneering research puts forth original perspectives on the intersection of AI and aesthetics to invigorate rural culture. It advocates holistic integration of technology and emphasizes AI's potential as a creative enabler versus replacement. Ultimately, it lays the groundwork for further exploration of leveraging AI innovations to empower rural communities. This timely study contributes to growing interest in emerging technologies to address critical issues facing rural China.

cs.CY↗