Exploratory Analysis of Motion Sickness Data: A Time Series Approach.

摘要

A methodology was developed in order to characterize the prodigious amount of electroencephalographic (EEG) data collected during motion sickness experiments at the Air Force Institute of Technology. The analog data are sampled and digitized into a time series. Stationary transformations and a windowing operation are performed on the data to produce local areas of stationarity. Windowed versions of the autocorrelation function, partial autocorrelation function and periodogram are discussed and employed. The windows are analyzed over time in order to view the underlying structure of the model that is hidden in the data. These functions are converted into image files to aid interpretation. The images are directly interpreted for model determination, model changes, artifact assessment and stationarity determination. A primary subject and two confirming subjects are analyzed. Both a placebo trial and Dilantin trial were analyzed for each subject to determine the nature of motion sickness and the efficacy of the drug treatment. The results are inconclusive as all three subjects brain data proved to be unique with respect to the placebo trials. Keywords: Theses. (kt)