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

GbyAI
GbyAI
Blog — PlanetScale
Blog — PlanetScale
The GitHub Blog
The GitHub Blog
Microsoft Security Blog
Microsoft Security Blog
I
InfoQ
A
About on SuperTechFans
T
The Blog of Author Tim Ferriss
D
DataBreaches.Net
L
LangChain Blog
F
Fortinet All Blogs
C
Check Point Blog
Google DeepMind News
Google DeepMind News
云风的 BLOG
云风的 BLOG
Engineering at Meta
Engineering at Meta
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
H
Help Net Security
J
Java Code Geeks
月光博客
月光博客
H
Hackread – Cybersecurity News, Data Breaches, AI and More
IT之家
IT之家
aimingoo的专栏
aimingoo的专栏
小众软件
小众软件
宝玉的分享
宝玉的分享
Jina AI
Jina AI

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
Secondary Inputs for Measuring User Engagement in Immersi...
David Murphy, Conor Higgins · 2019-10-04 · via cs.HC updates on arXiv.org

This paper presents an experiment to assess the feasibility of using secondary input data as a method of determining user engagement in immersive virtual reality (VR). The work investigates whether secondary data (biosignals) acquired from users are useful as a method of detecting levels of concentration, stress, relaxation etc. in immersive environments, and if they could be used to create an affective feedback loop in immersive VR environments, including educational contexts. A VR Experience was developed in the Unity game engine, with three different levels, each designed to expose the user in one of three different states (relaxation, concentration, stress). While in the VR Experience users physiological responses were measured using ECG and EEG sensors. After the experience users completed questionnaires to establish their perceived state during the levels, and to established the usability of the system. Next a comparison between the reported levels of emotion and the measured signals is presented, which show a strong correspondence between the two measures indicating that biosignals are a useful indicator of emotional state while in VR. Finally we make some recommendations on the practicalities of using biosensors, and design considerations for their incorporation in to a VR system, with particular focus on their integration in to task-based training and educational virtual environments.