Analysis of the possibilities of using EEG in assessing pilots’ psychophysical condition

Abstract

ANALYSIS OF THE POSSIBILITIES OF USING EEG IN ASSESSING PILOTS' PSYCHOPHYSICAL CONDITIONSummary. An excessive load on an operator's cognitive system can cause deterioration in perceptual abilities, decreased reaction time and increased probability of making an incorrect decision, which in turn can lead to a dangerous situation. Researching the cognitive load of an operator can therefore contribute to safer transportation. While there are many methods used in the study of cognitive load, they can be classified as either subjective assessments or objective assessments.This paper presents an analysis of the possibilities of using electroencephalography in assessing the psychophysical condition of the pilot. The investigation was conducted in the Simulation Research Laboratory in the Institute of Combustion Engines and Transport at Poznan University of Technology.

Methodology of research on drivers perception at level crossings

“…The undeniable advantage of using simulators in scientific research is the opportunity to control as many factors as possible and record a number of variables, including the operator's physiological parameters and psychological state [9][10][11]. The use of simulators makes it possible to conduct studies that enable us to achieve complete standardisation of testing conditions [12]. The repeatability of the scenarios makes it possible to compare the behaviour of various operators in the same situation or the same operator in different situations, which is not possible in actual traffic conditions.…”

Assessing the information flows and established their effects on the results of driver’s activity

“…The study used a monopolar recordthe activity of one tap at an electrically neutral point (Desimone & Duncan, 1995). In the Cardiosens system, a digital 3-channel microprocessor-based cardiograph is used as a portable ECG monitor recorder, recording an electronic Archives of Transport, 45(1), [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]2018 signal to a removable SD/MMC flash card (Zhuk et. al,, 2017).…”

“…Dependence of the change in the time of distraction of the tester from the performance of the main activity (  ), taking into account the specific gravity of the Delta-rhythm (  ) ( Figure 6) and thetarhythm (  ) (Figure 7), which reflect the inhibitory processes in the cerebral cortex from full power signal, to which the signals of , , , ,      -Archives of Transport, 45(1), [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]2018 rhythms are related, are linear in nature and indicate that as the percentage of signals from these rhythms increases, the time of abstraction from performing the main activity increases. Further, statistical equations and regression methods were used to derive linear equations (5)(6)(7)(8) and build the dependences ( Figures 6-9) of the time of abstraction from the performance of the main activity, taking into account the quantitative characteristics of the prevalence of excitatory and inhibitory processes in the cerebral cortex: fast (β + γ) and slow (δ + θ) rhythms of the EEG, as well as the forces of exciting and inhibitory processes in the cerebral cortex: fast (β -γ) and slow (δ -θ) EEG rhythms.…”

“…The given regression equations have statistical significance, while the value of the linear correlation tends to 1, which for equations (3)(4)(7)(8) indicates the presence of a direct linear relationship between the variables considered, and for equations (1-2, 5-6, 9-10) of the inverse linear connection. The calculated value of Fisher's criterion for models of changing the time of abstraction from the Archives of Transport, 45(1), [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]2018 performance of the main activity, taking into account the EEG indices (1-10) reflects the informative nature of the model, while the average approximation error is large enough; however, in the framework of the study, the construction of these models is necessary for determining the character of the dependence in constructing a general mathematical model of influence of information flows, which is displayed by EEG indicators, for the time of distraction from the performance of the driver's primary activity.…”

“…Compared with the model (11), the value of the average error of approximation which is 10.86 %, we see that by incorporating ECG in the model (12), managed to get a more accurate model of the impact of information flows at the time of driver distraction from performing its core activities. [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]2018 The results of the assessment of the overall impact of the model information flow at the time of driver distraction from the main activity, considering the performance of EEG and ECG showed next indicators: the Multiple correlation coefficient -99,11 %; The average error of approximation -9,32%; Fisher's exact test: settlement -913,1; tabular-2,46. Based on the data shown in Table 4, it's calculated Fisher criterion more table index.…”