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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
An Investigation of the Incidences of Repetitive Strain I...
Olatunde Olabiyisi, Yusuff Akingboye, Adebayo Abayomi-Alli, Fred · 2013-08-27 · via cs.HC updates on arXiv.org

Computer has been incorporated into day to day activities of almost every field of human endeavour, offices to different shops. Therefore many people are now working with computer for longer hours of time. There is no doubt that this incorporation of computer has helped users a lot but it also brings problems to the users. One of the problems is Repetitive Strain Injury (RSI). Five hundred and thirty one (531) questionnaires were personally administered to different categories of people that use computer in various works of life, ranging from banking sector, civil service, educational sector, health sector to private sector. The distribution cut across different professions. A statistical analysis was conducted on the data obtained using frequency distribution, Pearson Correlation and Linear Regression. The result obtained showed that 94.3% of the respondents suffered pain from one or more parts of the body. 86.8% of the respondents suffered from eyestrain, 63.9% suffered from low back pain, 67.4% with wrist pain, 64.7% finger pain while the least suffered pain was foot pain which only 19% responded positively to it. There are significant relationships between duration of computer usage, type of chair used, type and size of monitor used and the incidence of RSI. RSI modeled was formulated through linear regression which showed that a unit change in computer will result in corresponding 1.76 unit increases in RSI and a unit change in ergonomic deficiency will also result in corresponding 0.66 increases in RSI. The existence of RSI was established and it was discovered that the more time spent on the computer system, the more the proximity of having strain or pain in one or more part(s) of the body.