Analyzing the cognitive performance of air traffic controllers using psychophysiological responses

Abstract

Introduction: Air traffic control is considered as one of the stressful jobs. In anxiogenic and stressful world, the maintenance of an optimal cognitive performance is a constant challenge. It is particularly true in complex working environments e.g. air traffic control , where individuals have sometimes to cope with a high mental workload (MWL) and stressful or unexpected situations. By monitoring the occurrence of such states, serious consequences of performance breakdown can be prevented. The psychophysiological measures reflect the information regarding various human performance status. If this scientific assessment tools and methods are used in field research, their findings may be more valuable than research conducted in a laboratory. Thus, the present study was conducted in order to analyzing the cognitive performance of air traffic controllers using psychophysiological responses. Methods: A cross-sectional comparative study was conducted on 20 professional air traffic controllers. EEG and ECG signals recorded while controllers performed cognitive tasks [A-X Continuous Performance Test (AX-CPT) and 3-back working memory task] after they were exposed to two levels of task difficulty (high and low MWL) in the morning and afternoon. MWL was assessed in these two levels of task difficulty by NASA-TLX questionnaire. Data were first recorded and stored using the software BioTrace + software®, Mind Media BV, Roermond-Herten, The Netherlands and further exported in MAT file format to Matlab R2017a for the next offline processing. Statistical analysis of the data was performed using SPSS software version 23.0. Results: The results demonstrated that cognitive performance varied over time as a function of mental workload levels. The findings confirmed the sensitivity of ECG features to time of day. Also, the NN20 was influenced by MWL in the 3-back task (p < 0.05). The results confirmed the sensitivity of the theta and beta activities to levels of task difficulty in the 3-back task, while they were not affected in the AX-CPT. Theta and beta activities were influenced by time of day in the AX-CPT. The mixed model ANOVA showed that correct responses were associated with the mean HR in the AX-CPT task (P = 0.030). In the 3-back task, commission errors were correlated with alpha activity in the parietal region. The results showed that commission errors and correct responses were associated with the delta and theta activity in the parietal region, respectively (P = 0.011, P = 0.001). According to the results, there is an agreement between the correct responses and response time with ECG and EEG features in the 3-back and AX-CPT tasks. Conclusions: The findings of the study showed that high MWL could result in a decreased cognitive performance, and that this decrease is higher in the afternoon than in the morning. From a physiological perspective, our findings confirmed sensitivity of the ECG features to time of day. Also, the findings highlight the important role of EEG activity in response to task difficulty levels during the day. The findings provide guidance for application of changes in psychophysiological measures when MWL level is manipulated during the day that could be implemented in future for the development of real-time monitoring systems to improve aviation safety.