Autonomic nervous system factors underlying anxiety in virtual environments: a regression model for cybersickness

Susan Bruck; Paul A. Watters

doi:10.1109/VSMM.2009.16

Autonomic nervous system factors underlying anxiety in virtual environments: a regression model for cybersickness

Susan Bruck, Paul A. Watters

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

8 Citations (Scopus)

26 Downloads (Pure)

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.

Original language	English
Title of host publication	2009 15th International Conference on Virtual Systems and Multimedia
Subtitle of host publication	proceedings : VSMM 2009 : 9-12 September 2009 Vienna, Austria
Editors	Robert Sablatnig, Martin Kampel, Martin Lettner
Place of Publication	Los Alamitos, Calif.
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	67-71
Number of pages	5
ISBN (Print)	9780769537900
DOIs	https://doi.org/10.1109/VSMM.2009.16
Publication status	Published - 2009
Externally published	Yes
Event	International Conference on Virtual Systems and MultiMedia (15th : 2009) - Vienna Duration: 9 Sept 2009 → 12 Sept 2009

Conference

Conference	International Conference on Virtual Systems and MultiMedia (15th : 2009)
City	Vienna
Period	9/09/09 → 12/09/09

Bibliographical note

Copyright 2009 IEEE. Reprinted from 2009 15th International Conference on Virtual Systems and Multimedia : proceedings : VSMM 2009 : 9-12 September 2009 Vienna, Austria. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Macquarie University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

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10.1109/VSMM.2009.16

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Bruck, S., & Watters, P. A. (2009). Autonomic nervous system factors underlying anxiety in virtual environments: a regression model for cybersickness. In R. Sablatnig, M. Kampel, & M. Lettner (Eds.), 2009 15th International Conference on Virtual Systems and Multimedia: proceedings : VSMM 2009 : 9-12 September 2009 Vienna, Austria (pp. 67-71). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/VSMM.2009.16

Bruck, Susan ; Watters, Paul A. / Autonomic nervous system factors underlying anxiety in virtual environments : a regression model for cybersickness. 2009 15th International Conference on Virtual Systems and Multimedia: proceedings : VSMM 2009 : 9-12 September 2009 Vienna, Austria. editor / Robert Sablatnig ; Martin Kampel ; Martin Lettner. Los Alamitos, Calif. : Institute of Electrical and Electronics Engineers (IEEE), 2009. pp. 67-71

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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.",

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note = "Copyright 2009 IEEE. Reprinted from 2009 15th International Conference on Virtual Systems and Multimedia : proceedings : VSMM 2009 : 9-12 September 2009 Vienna, Austria. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Macquarie University{\textquoteright}s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.; International Conference on Virtual Systems and MultiMedia (15th : 2009) ; Conference date: 09-09-2009 Through 12-09-2009",

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Bruck, S & Watters, PA 2009, Autonomic nervous system factors underlying anxiety in virtual environments: a regression model for cybersickness. in R Sablatnig, M Kampel & M Lettner (eds), 2009 15th International Conference on Virtual Systems and Multimedia: proceedings : VSMM 2009 : 9-12 September 2009 Vienna, Austria. Institute of Electrical and Electronics Engineers (IEEE), Los Alamitos, Calif., pp. 67-71, International Conference on Virtual Systems and MultiMedia (15th : 2009), Vienna, 9/09/09. https://doi.org/10.1109/VSMM.2009.16

Autonomic nervous system factors underlying anxiety in virtual environments: a regression model for cybersickness. / Bruck, Susan; Watters, Paul A.
2009 15th International Conference on Virtual Systems and Multimedia: proceedings : VSMM 2009 : 9-12 September 2009 Vienna, Austria. ed. / Robert Sablatnig; Martin Kampel; Martin Lettner. Los Alamitos, Calif.: Institute of Electrical and Electronics Engineers (IEEE), 2009. p. 67-71.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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N1 - Copyright 2009 IEEE. Reprinted from 2009 15th International Conference on Virtual Systems and Multimedia : proceedings : VSMM 2009 : 9-12 September 2009 Vienna, Austria. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Macquarie University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

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N2 - 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.

AB - 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.

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Y2 - 9 September 2009 through 12 September 2009

ER -

Bruck S, Watters PA. Autonomic nervous system factors underlying anxiety in virtual environments: a regression model for cybersickness. In Sablatnig R, Kampel M, Lettner M, editors, 2009 15th International Conference on Virtual Systems and Multimedia: proceedings : VSMM 2009 : 9-12 September 2009 Vienna, Austria. Los Alamitos, Calif.: Institute of Electrical and Electronics Engineers (IEEE). 2009. p. 67-71 doi: 10.1109/VSMM.2009.16

Autonomic nervous system factors underlying anxiety in virtual environments: a regression model for cybersickness

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