A Physiological Model of Cybersickness during Virtual Environment Interaction

Abstract

The challenges of measuring, managing, and predicting negative side effects (i.e. cybersickness) during virtual environment (VE) interaction and unwanted aftereffects continue to persist. Most assessments have been limited to subjective questionnaires. This study investigated the effects of VE interaction on nausea (gastric activity) and the development of a quantitative model affording cybersickness prediction. This cybersickness state estimation model (CSEM) offers a quantitative (i.e. physiological based) predictability to cybersickness. The model relates time, recordable gastric activity using electrogastrogram (EGG) measures as a physiological predictor and subjective sickness estimates. This work employs neural network algorithms to model user state associated with cybersickness. Neural network models were designed, trained, and tested to determine the network trainability and accuracy. Mean SSQ total severity scores indicate significant differences between conditions. All CSEM models had a low sum of squared error. The models were found to be accurate in predicting cybersickness from unseen data.

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References

Casali

J. G.

(1985). Vehicular simulator-induced sickness. Volume 1. NTSC TR86-010 AD-A173 904, Naval Training Systems Center, Arlington, VA. Claremount C., A. (1931). Psyche 11. 86–90.

Stern

R. M.

(1999). The retention of adaptation and motion sickness eliciting stimulation. Aviation, Space, and Environmental Medicine, 70 (8), 766–768.

Kennedy

R. S.

Stanney

K. M.

Dunlap

W. P.

(2000). Duration and Exposure to Virtual Environments: Sickness Curves During and Across Sessions. Presence: Teleoperators and Virtual Environments, 9 (5), 463–472.

Kennedy

R. S.

Fowlkes

J. E.

(1992). Simulator sickness is polygenic and polysymptomatic: Implications for research. International Journal of Aviation Psychology. 2 (1), 23–38.

McCauley

M. E.

Sharkey

T. J.

(1992). Cybersickness: Perception of self-motion. Presence Teleoperators and Virtual Environments 1 (4), 375–403.

Miller

J. C.

Sharkey

T. J.

Graham

G. A.

McCauley

M. E.

(1993). Autonomic Physiological data associated with simulator discomfort. Aviation, Space, and Environmental Medicine, 64 (9), 813–819.

Nichols

S. C.

Cobb

Wilson

J. R.

(1997). Health and safety implications of virtual environments: Measurement issues. Presence: Teleoperators and Virtual Environments, 6 (6), 667–675.

Owen

D. H.

(1990). Perception and control of changes in self-motion. A functional approach to the study of information and skill. In Warren

Wertheim

A. H.

Perception & Control of Self-Motion. (pp. 289–326). Hillsdale, NJ: Lawrence Erlbaum Associates.

Regan

E. C.

(1995). Some evidence of adaptation to immersion in virtual reality Displays, 16 (3), 135–139.

10.

Roberts

W. K.

Ntuen

(1998) Perception of Loss in Altitude during Low-Altitude Flight. Proceedings of the 42nd Annual Meeting of the Human Factors and Ergonomics Society.

11.

Smith

(1993) Neural networks for statistical modeling, Van Nostrand Reinhold, New York.

12.

Stanney

K. M.

Kennedy

R. S.

(2001). Motion sickness in virtual environments. Karwowski

International Encyclopedia of Ergonomics and Human Factors. Taylor and Francis.

13.

Stanney

K. M.

Kennedy

R. S.

Drexler

J. M.

Harm

D. L.

(1999). Motion sickness and proprioceptive aftereffects following virtual environment exposure. Applied Ergonomics, 30, 27–38.

14.

Stanney

K. M.

Kennedy

R. S.

Drexler

J. M.

(1997). Cybersickness is not simulator sickness. 41st Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 1138–1142.

15.

Stoffergen

T. A.

Riccio (1991). An ecological critique of sensory conflict theory of motion sickness. Ecological Psychology, 3, 159–194.

16.

Zurada

J. M.

(1992). Introduction to Artificial Neural Systems, West publishing Company, New York.