Why the Driver is Never Sick: The Role of Control and Gender in V.I.M.S. Kelly Vitatoe, Jennifer Shinkle, Meghan Capistrano, Erin Taute, Rachel Burgard & L. James Smart (faculty Advisor) Department of Psychology

Background •Through research and innovation engineers have produced better vehicles, boats, and planes that suppress

the motion characteristics that make people motion sick (though not intentionally) •While the virtual reality world expands, better technology (software/hardware) has produced more motion sick-

ness •The Experience of Motion Sickness

Instability, Dizziness, Nausea, Fatigue (Sophite Syndrome) – just to name a few Sensory Conflict Theory •Probably the most well known and intuitive theory – has been around since the Ancient Greeks. •Asserts that Motion sickness is produced when the brain receives information from different senses unsynchro-

nized with each other (reporting different motion ‘realities’) •While the Brain attempts to resolve this conflict, one can become motion sick (Reason, 1978; Oman, 1982) Postural Instability Theory •Despite it’s intuitive appeal, Conflict Theory does not provide an objective measure of conflict, nor does it allow

sickness to be predicted a priori •PI Theory asserts Motion Sickness is not related to a sensory conflict, but instead a decreased ability to appro-

priately control one’s postural motion (Riccio & Stoffregen, 1991) •The longer one remains unstable – the more likely that sickness will occur •Research has shown that postural motion can predict sickness (Stoffregen & Smart, 1998; Stoffregen, et al,

2000; Smart, Stoffregen, & Bardy, 2002). Role of Behavior •PI theory places emphasis on understanding behavior and how we control it •Control is dependent on the pick up of relevant information as well as the appropriate coordination of actions

(perception-action cycle; Gibson, 1979) •Under many circumstances this control is prospective (forward planning/proactive) in nature, i.e., we gather in-

formation to organize our next set of actions (Gibson & Pick, 2000; Reed, 1996). •However, there are situations where the person must engage in reactive behaviors (e.g., back seat of a car,

watching movement in a film or video game). These actions may be qualitatively different from proactive behaviors (Rolnick & Lubow, 1991; Smart, Mobley, Otten, Smith, & Amin, 2004).

Role of Gender • A common report in the motion sickness literature is that women tend to report more sickness then men. • While there are several theories (cultural, hormonal, anatomical, etc.) regarding why women appear to be

more susceptible to motion sickness, the literature has not yielded any conclusive evidence supporting any of these perspectives (Flanagan, May, & Dobie, 2005).

• From a postural control perspective, there is no evidence that men and women regulate motion differently, however, the may be differences in how men and women respond to a visual disturbance.

Research questions & Hypotheses •The specific goal of the study is to determine the roles of control (the ability to modify the stimuli) and gender

on the occurrence of motion sickness,. •We expect passengers to exhibit greater head motion variability relative to the drivers’ motion (resulting from

the passenger having to behave reactively as opposed to the proactive behaviors that are afforded the driver) •As a consequence of this increased motion, we expect the passengers to exhibit more symptoms of motion

sickness. •We expect that the type of movements exhibited by the participants will vary as a function of their role (driver/

passenger) and potentially gender (male/female) during a given session.

Methods Participants •Sixteen (8 males, 8 females) were run in same-gender pairs •All participants had normal or corrected-to-normal vision and were in good health with no history of inner ear

(vestibular) dysfunction or dizziness/falls •Participants were required to come for two consecutive sessions and were paid for their participation. •Participants were aware that there was a chance that they would become motion sick. • Materials Head Mounted Display: Two virtual i*glasses SVGA 3D ASO1317 (I-O display systems, CA) personal displays

were used to present the virtual environment. Joystick: Microsoft sidewinder gamepad was used to control movement within the VE Motion Tracker: body movement was tracked using a magnetic tracking system (Flock of Birds, Ascension,

Inc.) Four sensors were used (see Fig. 1). Motion was sampled at 40 Hz.

Stimulus Driving Simulation: A commercial driving simulation (Need for Speed, Electronic Arts, Inc.) was used for the

control and experimental trials, the same track was used for all conditions (the track was reversed for the sec-ond session).

See Figure 2 for screenshots of stimuli

•Sensor IV- Passenger Head

•Sensor III– Driver Head

•Sensor II– Passenger Lower Spine

•Sensor I– Driver Lower Spine

Demo Stimulus (non-interactive) Experimental Stimulus (interactive)

Figure 2. Screenshots of Stimuli

Procedure •Participants were told the nature of the study and were asked to fill out a consent form,

demographics sheet, and a Simulator Sickness Questionnaire (SSQ, Kennedy & Lane, 1993)

•Participants were asked to perform two balance checks before beginning the experi-ment (these were repeated before participants were allowed to leave).

•Participants were seated on a stool 2.76 m from the laboratory wall and the sensors were placed on their body.

•Participants in each session were presented with three types of trials: 2 baseline (20 sec; no stimuli), 4 control (60 sec; Driver and Passenger passive), and 4 experimen-tal (300 sec; Driver active, Passenger passive).

Analysis Data & Analyses: • Motion data was collected in six axes of motion (AP, Lateral, Vertical, Roll, Pitch, & Yaw) for each sensor. • We analyzed the SSQ to determine whether the simulation produces symptoms of sickness. • We analyzed the variability, velocity, and range of head movement in the AP and Lateral,

axes for both the 300 second and 60 second trials. • We used a fractal analysis (dispersion) to help determine whether the postural motion dif-

fered qualitatively across control and gender variations. • We analyzed the correlation between head motion of the driver and passenger for the same three axes.

References and Acknowledgments Bassingthwaighte, J. B., Liebovitch, L. S., West, B.J. (1994). Fractal Physiology. New York, NY: Oxford University Press, Inc. Flanagan, M. B., May, J. G., & Dobie, T. G. (2005). Sex differences in tolerance to visually-induced motion sickness. Aviation, Space, and Environmental Medi-

cine, 76 (7), p. 642-6.

Gibson, E. J., & Pick, A. D. (2000). An Ecological Approach to Perceptual Learning and Development. Oxford: Oxford University Press.

Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Boston: Houghton-Mifflin, Inc.

Kennedy, R. S., Lane, N. E., Berbaum, K. S., & Lilienthal, M. G. (1993). Simulator sickness questionnaire: An enhanced method for quantifying simulator sick-

ness. International Journal of Aviation Psychology, 3, 203-220.

Oman, C.M. (1982). A heuristic mathematical model for the dynamics of sensory conflict and motion sick ness. Acta Otolaryngol. 44 (suppl. 392), 1—44.

Reason, J.T. (1978). Motion sickness adaptation: A neural mismatch model. J. R. Soc. Med., 71, 819— 829.

Reed, E. S. (1996). Encountering the World: Towards an Ecological Psychology. Mahwah; Lawrence Erlbaum.

Riccio, G. E., & Stoffregen, T. A. (1991). An ecological theory of motion sickness and postural instability. Ecological Psychology, 3, 195-240.

Rolnick, A., & Lubow, R. E. (1991). Why is the driver rarely motion sick? The role of controllability in motion sickness. Ergonomics, 34 (7), 867 – 879.

Smart, L. J., Mobley, B. S., Otten, E. W., Smith, D. L., & Amin, M. R. (2004). Not just standing there: the use of postural coordination to aid visual tasks. Hu-

man Movement Science 22 (6), 769-780.

Smart, L. J., Stoffregen, T. A., & Bardy, B. G. (2002). Visually induced motion sickness predicted by postural

instability. Human Factors, 44 (3), 451-465.

Stoffregen, T. A., Hettinger, L. R., Haas, M. W., Roe, M., & Smart, L. J. (2000). Postural instability and motion

sickness in a fixed-base flight simulator. Human Factors, 42 (3), 458-469.

Stoffregen, T. A., & Smart, L. J. (1998). Postural instability precedes motion sickness. Brain Research Bulletin, 47(5), 437-448.

This research is supported by a Crannell Award from the Department of Psychology.

Figure 1. Set up and Materials

SSQ: • Only 2 participants (both passengers) reported becoming sick. • A Kruskal-Wallis (non-parametric) test showed both non-significant pre-exposure scores and

non-significant post-exposure scores for the total SSQ scale, as well as the nausea, oculo-motor, and disorientation subscales when comparing the verbal reports of the driver versus the passenger.

• While no statistics were run comparing sick vs. well participants (due to sample size), SSQ scores for participants who reported motion sickness were elevated relative to the well par-ticipants.

Variability, Velocity, and Range: • Baseline: A main effect of gender was found in AP velocity, indicating that men moved

faster than women. • Control: A main effect of gender was found in AP variability, velocity, and range, indicating that men were higher than women in all three measures. A main effect of vision was found in AP variability and range, indicating that with

eyes closed people moved more than with eyes open. • Experimental: Variability: A task x gender interaction was found in AP, indicating that male drivers moved less than male passengers, and female drivers moved more than female passengers. Velocity: A task x gender interaction was found in AP, indicating that male drivers moved faster than male passengers, and female drivers moved slower than female passengers. A main effect of task was found in Lateral, indicating that drivers moved slower than passengers.

Correlations: • A correlation between the head movement in the AP direction and Lateral direction (separately) found a significant

difference between the male participants and the female participants in the AP direction for the experimental (300 second) trials, t(74) = 2.63, p = .01.

• However, the means indicated that the overall correlations were near zero, suggesting that the driver and passen-ger’s head motion was not strongly correlated.

• Cross correlations may help to determine the relation between the driver and passenger head motion, and will be conducted in future analyses.

Discussion • Traditional measures, which typically can only provide an overall representation of the behavior, showed differ-

ences in both gender and task. • However, the dispersion analysis, revealed that gender did not significantly influence postural control (motion)

while task differences did. • This is significant because the dispersion analysis provides an indication of the behavior over time (process). • Surprisingly, when active, participants’ motion was less uniform (indicating decreased stability) than when they

were passive. • However, these findings may reflect the anecdotal observations that many participants’ struggled to successfully

perform the task, possibly due to the mode of control. • This possibility along with the lack of gender differences in the dispersion analyses emphasizes the importance of

the quality of the interaction for adapting to novel environments. • In summary, task, more than gender, seems to play a larger role in determining behavior.

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Dispersion (fractal) Analysis: • Dispersion analysis is a type of fractal analysis that can be used to examine the similarity of measured data across

various time scales. • This analysis calculates the log of the variance (relative dispersion, RD) at multiple time scales and compares them to

the log of the time scales. The slope of a linear regression line determined by the log-log relationship can be used to calculate the fractal D using the equation D = 1-slope (Figure 6).

• The value of D can vary between 1 and 1.5, with values near 1 indicating uniformity over all time scales and values near 1.5 indicating random uncorrelated noise.

• As the value of D increases, it indicates that the larger times scales do describe the data in a similar manner as the smaller time scales (Bassingthwaighte, Liebovitch, & West, 1994).

• In the area of postural sway, values of D near 1.5 would indicate instability, while values near 1 would indicate stability. • The dispersion analysis was conducted on the experimental trials only.

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Figure 3. AP velocity differences for experimental trials.

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Figure 4. Lateral velocity differences for experimental trials.

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Figure 5. AP variability differences for experimental trials.

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Figure 7. AP Dispersion value differences for experimental trials.

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Figure 8. Lateral Dispersion value differences for experimental trials.

y = -0.1296x + 0.599

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Figure 6. Representative example of Dispersion analysis.

Dispersion results: • A main effect of task was found in both AP and

Lateral motion, indicating that when the participants were drivers, their motion was less uniform than when they were passengers.

• There were no differences in gender.