Chaos and Brain Wave Activity: Measures of Irregular Time Series
Abstract
Physiological measurements of the electrical activity of the brain may provide the predictive information necessary for a sensitive measure of the attention state of an airplane pilot or air traffic controller. Herein we review data processing techniques that have been developed in the past decade in the emerging area of dynamic systems theory and apply them to EEG time series data. The methods have been successfully used to interpret the dynamic content of a number of irregular time series and to aid in the construction of relatively simple mathematical descriptions of such systems, a number of which are reviewed herein. We demonstrate the feasibility of applying these algorithms to EEG time series data to determine its fractal (fractional) dimension, it is shown that the fractional dimension can be used as an indicator of various states of brain activity, having its lowest value for deep sleep and its highest value for eyes open, awake response, with an apparently monotonic increase with task complexity from one extreme to the other. Thus, within certain limits, the fractal dimension of an EEG can be associated with wakeful attentiveness and therefore used to assess the state of the operator in these information rich situations, e.g. pilots, air traffic controllers, radar observers, etc.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1988
- Accession Number
- ADA357643
Entities
People
- Bruce J. West