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Predicting motion sickness during parabolic flight.

Deborah L Harm1, Todd T Schlegel

  • 1Neurosciences Laboratory, NASA Johnson Space Center, Houston, TX 77058, USA. dharm@ems.jsc.nasa.gov

Autonomic Neuroscience : Basic & Clinical
|July 23, 2002
PubMed
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Predicting motion sickness severity is challenging. Researchers found that combining salivary amylase, R-R intervals, and a sympathovagal index accurately classified individuals into different motion sickness groups.

Area of Science:

  • Physiology
  • Human Factors

Background:

  • Individual susceptibility to motion sickness varies significantly.
  • Previous attempts to predict motion sickness have yielded limited success.

Purpose of the Study:

  • To investigate gender differences in physiological markers.
  • To evaluate the predictive potential of salivary markers and cardiovascular parameters for motion sickness severity.

Main Methods:

  • 16 subjects (10 men, 6 women) experienced parabolic flights.
  • Saliva samples (amylase, total protein) and cardiovascular data (R-R intervals, sympathovagal index) were collected.
  • Motion sickness symptoms were recorded during flight.

Main Results:

  • No significant gender differences were observed in sickness severity or measured physiological variables.
Keywords:
NASA Center JSCNASA Discipline Neuroscience

Related Experiment Videos

  • Discriminant analysis combining salivary amylase, R-R intervals, and sympathovagal index achieved 87% classification accuracy.
  • A significant Wilks' lambda coefficient (0.36, p=0.006) indicated successful classification.

    • Conclusions:

    • Resting levels of salivary amylase, high-frequency R-R interval data, and a sympathovagal index can effectively predict motion sickness severity.
    • This combination of biomarkers offers a promising approach for classifying individuals based on their susceptibility.