- Title
- Autonomic nervous system factors underlying anxiety in virtual environments : A regression model for cybersickness
- Creator
- Bruck, Susan; Watters, Paul
- Date
- 2009
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/35094
- Identifier
- vital:2301
- Identifier
-
https://doi.org/10.1109/VSMM.2009.16
- Identifier
- ISBN:9780769537900
- Abstract
- The ability to predict whether people will experience anxiety is important for recruitment and selection in highly-stressful professions. Using a Virtual Reality Environment (VRE) can provide a tool to predict whether a person will experience anxiety. This paper reports several regression models which suggest observed and self-reported measures of anxiety during and after immersion in a VRE can be used to predict an individual's anxiety response to a simulated stressful environment. We found that respiration was a poor predictor of anxiety, but that cardiac activity accounted for around 39% of variance in self-reported anxiety responses using a four point scale. In contrast, responses from the Simulator Sickness Questionnaire (SSQ) accounted for 98% of variance in anxiety responses. However, only four out of eighteen measures in the SSQ made a significant contribution to the model. The implication for predicting an individual's anxiety responses using self-report or physiological measures is discussed. © 2009 IEEE.
- Publisher
- Vienna :
- Relation
- Paper presented at VSMM 2009 -15th International Conference on Virtual Systems and Multimedia, Vienna : 9th-12th September 2009 p. 67-72
- Rights
- Copyright IEEE
- Rights
- This metadata is freely available under a CCO license
- Subject
- Cybersickness; Respiration; Virtual reality
- Full Text
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