Methods of analyses of biological time series are presented and compared to the traditional techiiiques based on the Fourier transform. Paranietric methods are used for computation of the autoregressive estimator, for the model order selection and for the spectrum estirnation. A nonlinear analysis deals with the state-space trajectory reconstruction and with the fractal and embedding dirnension estirnation. Experimental resiilts compare the abilities of traditional, pararnetric and nonlinear methods to distinguish different cognitive States of the human operator by an analysis of an EEG curve.
Impaired wakefulness of machine operators presents a danger not only for themselves, but often for the public at large as well. While on duty, such persons are expected to be continuously, i.e. without interruption, on the alert. For that purpose, we designed and carried out an experimental model of continuous vigilance monitoring using electroencephalography (EEG) and reaction time measured as the latency of the volunteers’ reaction to a sound stimulus. In this article, we focus on two different approaches of EEG signal analysis. Spectral analysis, which is based on linear stochastic approach, is the hrst type. On the other hand, there is nonlinear analysis formally called the chaos theory. For both methods, we will show typical markers which represent the state of the vigilance. Both methods will be compared and the outputs will be discussed.
Impaired wakefulness in machine operators poses a danger not only
to themselves but often also to the public at large. While on duty, such persons are expected to be continuously, i.e., without interruption, on the alert. For that purpose, we designed and carried out an experimental model of continuons vigilance monitoring using electroencephalography (EEG) and reaction time measured as the latency of the probanďs reaction to sound. If constructed, the set together with other logical elements and an alarm can make for an automatic detection of vigilance and, possibly, also of arousal stimuli in cases of microsleep. We have found the following new facts and coníirmed the validity of some of the earlier ones.
The article addresses the overwhelming problematics of attention decrease of human operators. It presents two sets of experiments used for vigilance detection and possible microsleep prediction. In the hrst experiment, the analysis of the electroencephalographic activity (EEG) of a human operátor (proband) is correlated with the reaction time (RT) to the sound stimulus. For the second set of experiments, the cooperation of a car simulator realized in virtual reality (VR) environment and measurement of EEG is presented. The paper introduces two main methods of the analysis of EEG: frequency analysis and nonlinear analysis based on computation of the state-space trajectory. For the frequency analysis, the delta, theta, alpha and beta bands are computed and compared with nonlinear measures Largest Lyapunov Exponent (LLE) and Correlation dimension (CD). Finally, both experiments are compared and its outcomes are discussed.