VR Sickness Benchmark System

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By rose rouhani, narmada umatheva, jannik brockerhoff, behrang keshavarz, ernst kruijff, jan gugenheimer & bernhard riecke

Tackling VR Sickness: A Novel Benchmark System for Assessing Contributing Factors and Mitigation Strategies through Rapid VR Sickness Induction and Recovery

Abstract

This research intro­duces a novel VR sick­ness bench­mark system, designed to address the lack of stan­dard­ized tools for assess­ing and mit­i­gat­ing VR sick­ness. It aims to rec­tify the incon­sis­ten­cies and lim­i­ta­tions preva­lent in exist­ing VR sick­ness assess­ment and mit­i­ga­tion meth­ods, thereby facil­i­tat­ing more effec­tive and com­pa­ra­ble cross-study analyses.

This bench­mark system, cre­ated using Unity 3D, fea­tures two dis­tinct VR envi­ron­ments, small and large, designed as figure-eight racing tracks through roller-coaster-like move­ments. Key design ele­ments to induce VR sick­ness includ vary­ing speeds, direc­tional changes, ele­va­tion shifts. pas­sive par­tic­i­pant move­ment, and enhanced optic flow with visual ele­ments. The system also includes an in-VR sick­ness rating tool for real-time feedback.

Our research stud­ies aim to eval­u­ate the effec­tive­ness of four com­monly dis­cus­sion VR sick­ness mit­i­ga­tion tech­niques in the envi­ron­ments, aimed at (1) val­i­dat­ing the bench­mark system’s capa­bil­ity to induce and reduce VR sick­ness in a con­trolled manner, ensur­ing tem­po­rary, man­age­able symp­toms with rapid recov­ery times. This aspect is cru­cial for eth­i­cal research con­duct and par­tic­i­pant safety; and (2) sys­tem­at­i­cally eval­u­at­ing and com­par­ing dif­fer­ent VR sick­ness mit­i­ga­tion tech­niques, con­tribut­ing to stan­dard­iz­ing VR sick­ness assess­ment and enhanc­ing the reli­a­bil­ity and com­pa­ra­bil­ity of VR research. The bench­mark system’s adapt­abil­ity across var­i­ous research dimen­sions makes it a valu­able tool for VR devel­op­ers and researchers, enabling effi­cient test­ing of a wide range of para­me­ters and design iterations.

This project is part of Rose Rouhani’s MSc thesis, here’s Rose pre­sent­ing on the VR Sickness Benchmark Project:

Videos of the small and large envi­ron­ments, with the VR sick­ness mit­i­ga­tion tech­niques imple­mented in each can be found in this YouTube playlist. Below is one exam­ple for the Dynamic FOV reduc­tion method, all of them are listed on our YouTube playlist.

 

Preprint (of paper under review)

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4790891

Rouhani, R., Umatheva, N., Brockerhoff, J., Keshavarz, B., Kruijff, E., Gugenheimer, J., & Riecke, B. (2024). Tackling Vr Sickness: A Novel Benchmark System for Assessing Contributing Factors and Mitigation Strategies Through Rapid Vr Sickness Induction and Recovery (SSRN Scholarly Paper 4790891). https://doi.org/10.2139/ssrn.4790891
Rouhani, Rose. 2024. “Tackling VR Sickness: A Novel Benchmark System for Assessing Contributing Factors and Mitigation Strategies.” MSc Thesis, Vancouver, BC, Canada: Simon Fraser University. https://summit.sfu.ca/item/38058. (Download)

Visuals of the benchmark

Overview of small environment:

small env overview 1

Overview of large environment:

large env overview 1

In-VR sick­ness per­cent­age scale: 
sickness score interface 1

Participant during study:

participant 1

 

Open source Unity code of the VR Sickness Benchmark

We just pub­lished a freely avail­able open sources Unity ver­sion of the VR Sickness Benchmark on GitHub here: https://github.sfu.ca/ispace-lab/VRSickness_Benchmark — please reach out to Bernhard & Rose if anything’s unclear, you’d like to col­lab­o­rate on using or fur­ther improv­ing the bench­mark, get access to some of our data col­lected etc.

We’re cur­rently work­ing on an active loco­mo­tion ver­sion of the bench­mark system, as well as data analy­sis scripts, that we hope to add soon.

Overview of VR sick­ness bench­mark Unity project — this is the main overview you’ll need for using and adapt­ing the the bench­mark. It explains the key com­po­nents of the project, includ­ing the code on Github and the set­tings essen­tial for research. Watch to under­stand how to set up the envi­ron­ment, manage motion sick­ness reduc­tion tech­niques, and export data for analy­sis.

 

Overview of this Unity nausea score script. This is one of the most impor­tant scripts in this project which you would most likely be work­ing with espe­cially if you would like to change any­thing in your output files for this project.

 

Overview of the Unity script used for cre­at­ing the figure 8 loco­mo­tion pattern.