Visually Induced Motion Sickness Estimation and Prediction in Virtual Reality using Frequency Components Analysis of Postural Sway Signal

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dc.contributor.authorChardonnet, Jean-Rémyen_US
dc.contributor.authorMirzaei, Mohammad Alien_US
dc.contributor.authorMérienne, Frédéricen_US
dc.contributor.editorMasataka Imura and Pablo Figueroa and Betty Mohleren_US
dc.date.accessioned2015-10-28T06:31:56Z
dc.date.available2015-10-28T06:31:56Z
dc.date.issued2015en_US
dc.description.abstractThe paper proposes a method for estimating and predicting visually induced motion sickness (VIMS) occurring in a navigation task in a 3D immersive virtual environment, by extracting features from the body postural sway signals in both the time and frequency domains. Past research showed that the change in the body postural sway may be an element for characterizing VIMS. Therefore, we conducted experiments in a 3D virtual environment where the task was simply a translational movement with different navigation speeds. By measuring the evolution of the body's center of gravity (COG), the analysis of the sway signals in the time domain showed a dilation of the COG's area, as well as a change in the shape of the area. Frequency Components Analysis (FCA) of the sway signal gave an efficient feature to estimate and predict the level of VIMS. The results provide promising insight to better monitor sickness in a virtual reality application.en_US
dc.description.sectionheadersFull Papersen_US
dc.description.seriesinformationICAT-EGVE 2015 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environmentsen_US
dc.identifier.doi10.2312/egve.20151304en_US
dc.identifier.isbn978-3-905674-84-2en_US
dc.identifier.issn1727-530Xen_US
dc.identifier.pages9-16en_US
dc.identifier.urihttps://doi.org/10.2312/egve.20151304en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectH.1.2 [Models and principles]en_US
dc.subjectUser/Machine Systemsen_US
dc.subjectHuman information processing H.5.1 [Information Interfaces and Presentation]en_US
dc.subjectMultimedia Information Systemsen_US
dc.subjectArtificialen_US
dc.subjectaugmenteden_US
dc.subjectvirtual realities H.5.2 [Information Interfaces and Presentation]en_US
dc.subjectUser interfacesen_US
dc.subjectEvaluation/methodologyen_US
dc.titleVisually Induced Motion Sickness Estimation and Prediction in Virtual Reality using Frequency Components Analysis of Postural Sway Signalen_US
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