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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
Road to Serenity: Individual Variations in the Efficacy o...
A. J. Bequet, C. Jallais, J. Quick, D. Ndiaye, A. R. Hidalgo-Mun · 2024-06-14 · via cs.HC updates on arXiv.org

Stress impacts driving-related cognitive functions like attention and decision-making, and may arise in automated vehicles due to non-driving tasks. Unobtrusive relaxation techniques are needed to regulate stress without distracting from driving. Tactile wearables have shown efficacy in stress regulation through respiratory guidance, but individual variations may affect their efficacy. This study assessed slow-breathing tactile guidance under different stress levels on 85 participants. Physiological, behavioral and subjective data were collected. The influence of individual variations (e.g., driving habits and behavior, personality) using logistic regression analysis was explored. Participants could follow the guidance and adjust breathing while driving, but subjective efficacy depended on individual variations linked to different efficiency in using the technique, in relation with its attentional cost. An influence of factors linked to the evaluation of context criticality was also found. The results suggest that considering individual and contextual variations is crucial in designing and using such techniques in demanding driving contexts. In this line some design recommendations and insights for further studies are provided.