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

J
Java Code Geeks
F
Fortinet All Blogs
云风的 BLOG
云风的 BLOG
MyScale Blog
MyScale Blog
D
DataBreaches.Net
Stack Overflow Blog
Stack Overflow Blog
A
About on SuperTechFans
Google DeepMind News
Google DeepMind News
Microsoft Security Blog
Microsoft Security Blog
腾讯CDC
The GitHub Blog
The GitHub Blog
Jina AI
Jina AI
B
Blog RSS Feed
I
InfoQ
N
Netflix TechBlog - Medium
T
The Blog of Author Tim Ferriss
Microsoft Azure Blog
Microsoft Azure Blog
Recent Announcements
Recent Announcements
GbyAI
GbyAI
H
Help Net Security
L
LangChain Blog
M
MIT News - Artificial intelligence
Y
Y Combinator Blog
aimingoo的专栏
aimingoo的专栏

cs.HC updates on arXiv.org

A Framework for Measuring Appropriate Reliance on Set-Valued AI Advice DeliChess: A Multi-party Dialogue Dataset for Deliberation in Chess Puzzle Solving From Explanation to Diagnosis: Next Generation Interactive Video Coach with Misstep Awareness SocialCoach: Personalized Social Skill Learning with RL-based Agentic Tutoring and Practice Formalizing all indexed mathematics as a benchmark for general reasoning, with the example of implementing dilatations of categories Face versus Body Tracking for Human-Robot Interaction: An Egocentric Dataset From Prompt to Service: An SLM-Based Agent Orchestration Gateway for AI-Driven Virtual Worlds What LLMs Must Forget to Teach Effectively: A DIY Approach to Premodern Japanese Language Pedagogy 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 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
Eye Tracking to Understand Impact of Aging on Mobile Phon...
Antony William Joseph, Jeevitha Shree DV, Kamal Preet Singh Salu · 2021-01-04 · via cs.HC updates on arXiv.org

Usage of smartphones and tablets have been increasing rapidly with multi-touch interaction and powerful configurations. Performing tasks on mobile phones become more complex as people age, thereby increasing their cognitive workload. In this context, we conducted an eye tracking study with 50 participants between the age of 20 to 60 years and above, living in Bangalore, India. This paper focuses on visual nature of interaction with mobile user interfaces. The study aims to investigate how aging affects user experience on mobile phones while performing complex tasks, and estimate cognitive workload using eye tracking metrics. The study consisted of five tasks that were performed on an android mobile phone under naturalistic scenarios using eye tracking glasses. We recorded ocular parameters like fixation rate, saccadic rate, average fixation duration, maximum fixation duration and standard deviation of pupil dilation for left and right eyes respectively for each participant. Results from our study show that aging has a bigger effect on performance of using mobile phones irrespective of any complex task given to them. We noted that, participants aged between 50 to 60+ years had difficulties in completing tasks and showed increased cognitive workload. They took longer fixation duration to complete tasks which involved copy-paste operations. Further, we identifed design implications and provided design recommendations for designers and manufacturers.