Innovative Cybersickness Detection: Exploring Head Movement Patterns in Virtual Reality Salehi, Masoud Javadpour, Nikoo Beisner, Brietta Sanaei, Mohammadamin Gilbert, Stephen
dc.contributor.department Industrial and Manufacturing Systems Engineering
dc.contributor.department Virtual Reality Applications Center 2024-02-15T16:08:20Z 2024-02-15T16:08:20Z 2024-02-05
dc.description.abstract Despite the widespread adoption of Virtual Reality (VR) technology, cybersickness remains a barrier for some users. This research investigates head movement patterns as a novel physiological marker for cybersickness detection. Unlike traditional markers, head movements provide a continuous, non-invasive measure that can be easily captured through the sensors embedded in all commercial VR headsets. We used a publicly available dataset from a VR experiment involving 75 participants and analyzed head movements across six axes. An extensive feature extraction process was then performed on the head movement dataset and its derivatives, including velocity, acceleration, and jerk. Three categories of features were extracted, encompassing statistical, temporal, and spectral features. Subsequently, we employed the Recursive Feature Elimination method to select the most important and effective features. In a series of experiments, we trained a variety of machine learning algorithms. The results demonstrate a 76% accuracy and 83% precision in predicting cybersickness in the subjects based on the head movements. This study contribution to the cybersickness literature lies in offering a preliminary analysis of a new source of data and providing insight into the relationship of head movements and cybersickness.
dc.description.comments This is a preprint from Salehi, Masoud, Nikoo Javadpour, Brietta Beisner, Mohammadamin Sanaei, and Stephen B. Gilbert. "Innovative Cybersickness Detection: Exploring Head Movement Patterns in Virtual Reality." arXiv preprint arXiv:2402.02725 (2024). doi: Copyright 2024 The Authors. CC BY.
dc.language.iso en
dc.publisher arXiv
dc.source.uri *
dc.subject.disciplines DegreeDisciplines::Engineering::Risk Analysis
dc.subject.keywords Cybersickness
dc.subject.keywords Machine Learning
dc.subject.keywords Postural Sway
dc.subject.keywords Head Move-ments
dc.subject.keywords Windowing
dc.subject.keywords Fourier Transform
dc.subject.keywords Wavelet Transform
dc.subject.keywords Recursive Feature Elimination
dc.subject.keywords Time Series
dc.title Innovative Cybersickness Detection: Exploring Head Movement Patterns in Virtual Reality
dc.type Preprint
dspace.entity.type Publication
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relation.isOrgUnitOfPublication 51d8b1a0-5b93-4ee8-990a-a0e04d3501b1
relation.isOrgUnitOfPublication dad3cd36-0f8b-49c3-b43f-1df139ae2068
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