惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

aimingoo的专栏
aimingoo的专栏
腾讯CDC
Y
Y Combinator Blog
L
LangChain Blog
B
Blog
U
Unit 42
P
Proofpoint News Feed
G
Google Developers Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
博客园 - 【当耐特】
WordPress大学
WordPress大学
月光博客
月光博客
Vercel News
Vercel News
雷峰网
雷峰网
T
The Blog of Author Tim Ferriss
MyScale Blog
MyScale Blog
大猫的无限游戏
大猫的无限游戏
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
酷 壳 – CoolShell
酷 壳 – CoolShell
Blog — PlanetScale
Blog — PlanetScale
博客园 - 司徒正美
云风的 BLOG
云风的 BLOG
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
博客园 - 叶小钗

cs.HC updates on arXiv.org

Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video Vision-Language Models Suppress Female Representations Under Ambiguous Input The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace TUX: Measuring Human--AI Tacit Understanding LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support Roles How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality Analyzing Persona Effects in Generated Explanations from Multimodal LLM Agents in Urban Perception First head-to-head comparison of agentic AI applied to the analysis of simulated data of the Einstein Telescope Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering The Timing Dependencies of Trust: Speed, Accuracy, and cBCI Neuro-Decoupling in Human-AI Teams Bayesian Distributional Models of Executive Functioning Visual Matters: Connecting Aesthetic Appeal and Production Quality of Photos, Infographics and Data Visualizations to Credibility of Social Media Posts Data-driven Head Motion Generation through Natural Gaze-Head Coordination Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why Perceptually Lossless Tactile Texture Synthesis with Compact Spectral Envelope Models MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data CogAdapt: Transferring Clinical ECG Foundation Models to Wearable Cognitive Load Assessment via Lead Adaptation Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build PaintCopilot: Modeling Painting as Autonomous Artistic Continuation Personality Engineering with AI Agents: A New Methodology for Negotiation Research PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education Conversations in Space: Structuring Non-Linear LLM Interactions on a Canvas MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis nASR: An End-to-End Trainable Neural Layer for Channel-Level EEG Artifact Subspace Reconstruction in Real-Time BCI
Towards an Emotion-Aware Metaverse: A Human-Centric Shipb...
Musaab H. Hamed-Ahmed, Diego Ramil-López, Paula Fraga-Lamas, Tia · 2025-03-05 · via cs.HC updates on arXiv.org

Traditional XR and Metaverse applications prioritize user experience (UX) for adoption and success but often overlook a crucial aspect of user interaction: emotions. This article addresses this gap by presenting an emotion-aware Metaverse application: a Virtual Reality (VR) fire drill simulator designed to prepare crews for shipboard emergencies. The simulator detects emotions in real time, assessing trainees responses under stress to improve learning outcomes. Its architecture incorporates eye-tracking and facial expression analysis via Meta Quest Pro headsets. The system features four levels whose difficulty is increased progressively to evaluate user decision-making and emotional resilience. The system was evaluated in two experimental phases. The first phase identified challenges, such as navigation issues and lack of visual guidance. These insights led to an improved second version with a better user interface, visual cues and a real-time task tracker. Performance metrics like completion times, task efficiency and emotional responses were analyzed. The obtained results show that trainees with prior VR or gaming experience navigated the scenarios more efficiently. Moreover, the addition of task-tracking visuals and navigation guidance significantly improved user performance, reducing task completion times between 14.18\% and 32.72\%. Emotional responses were captured, revealing that some participants were engaged, while others acted indifferently, indicating the need for more immersive elements. Overall, this article provides useful guidelines for creating the next generation of emotion-aware Metaverse applications.