Collection and Statistical Analysis of Biophysical Data to Predict Motion Sickness Incidence

摘要

Biophysical data were collected on humam volunteers to study the effects of the motion sickness syndrome. Physiological parameters were analyzed by descriptive statistical methods and by means of a spectrum analyzer. Descriptive statistical analysis showed at least five separate physiological parameters were linearly correlated to a motion sickness symptom index. Spectral analysis showed definite frequency and amplitude shifts during the onset of motion sickness for various parameters. Low frequency brain wave activity on the order of 0.1 Hz was discovered as the subject approached nausea. A multiple linear regression model was constructed from the correlated data obtained by descriptive statistics. Six separate physiological parameters were useful in describing a predictive motion sickness model that can be used as a major construct in developing a complete biofeedback system for countering effects of motion sickness.