Dataset for predicting cybersickness from a virtual navigation task

2023/02/07 by Yuyang Wang, Wang, Yuyang, Ruichen Li +5
Psychology · Social Sciences · #Artificial Intelligence (cs.AI) #Digital Mental Health Interventions #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #I.2 #Impact of Technology on Adolescents #J.0 #J.3

paper · pdf · doi:10.48550/arxiv.2303.13527

openalex publication_date 2023/02/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This work presents a dataset collected to predict cybersickness in virtual reality environments. The data was collected from navigation tasks in a virtual environment designed to induce cybersickness. The dataset consists of many data points collected from diverse participants, including physiological responses (EDA and Heart Rate) and self-reported cybersickness symptoms. The paper will provide a detailed description of the dataset, including the arranged navigation task, the data collection procedures, and the data format. The dataset will serve as a valuable resource for researchers to develop and evaluate predictive models for cybersickness and will facilitate more research in cybersickness mitigation.

Related

• A Deep Cybersickness Predictor through Kinematic Data with Encoded Physiological Representation
• TruVR: Trustworthy Cybersickness Detection using Explainable Machine Learning
• Automatic Recommendation of Strategies for Minimizing Discomfort in Virtual Environments
• Physiology-driven cybersickness detection in virtual reality: a machine learning and explainable AI approach
• Mazed and Confused: A Dataset of Cybersickness, Working Memory, Mental Load, Physical Load, and Attention During a Real Walking Task in VR