Abstract
In our digitized society, advanced information and communication technology and highly interactive work environments impose high demands on cognitive capacity. Optimal workload conditions are important for assuring employee's health and safety of other persons. This is particularly relevant in safety-critical occupations, such as air traffic control. For measuring mental workload using the EEG, we have developed the method of Dual Frequency Head Maps (DFHM). The method was tested and validated already under laboratory conditions. However, validation of the method regarding reliability and reproducibility of results under realistic settings and real world scenarios was still required. In our study, we examined 21 air traffic controllers during arrival management tasks. Mental workload variations were achieved by simulation scenarios with different number of aircraft and the occurrence of a priority-flight request as an exceptional event. The workload was assessed using the EEG-based DFHM-workload index and instantaneous self-assessment questionnaire. The DFHM-workload index gave stable results with highly significant correlations between scenarios with similar traffic-load conditions (r between 0.671 and 0.809, p ≤ 0.001). For subjects reporting that they experienced workload variation between the different scenarios, the DFHM-workload index yielded significant differences between traffic-load levels and priority-flight request conditions. For subjects who did not report to experience workload variations between the scenarios, the DFHM-workload index did not yield any significant differences for any of the factors. We currently conclude that the DFHM-workload index reveals potential for applications outside the laboratory and yields stable results without retraining of the classifiers neither regarding new subjects nor new tasks.
Highlights
In our digitized society, advanced information and communication technology and highly interactive work environments impose high demands on cognitive capacity and on the ability to cope with increased task load (Kompier and Kristensen, 2001; Niosh, 2002; Landsbergis et al, 2003; Lohmann-Haislah, 2012)
In a laboratory study conducted with 54 subjects and during execution of wellestablished cognitive tasks, we developed the so-called Dual Frequency Head Maps (DFHM)
The implemented simulation scenarios differed regarding two factors that were responsible for mental workload variations of air traffic controllers as suggested by Averty et al (2004)
Summary
In our digitized society, advanced information and communication technology and highly interactive work environments impose high demands on cognitive capacity and on the ability to cope with increased task load (Kompier and Kristensen, 2001; Niosh, 2002; Landsbergis et al, 2003; Lohmann-Haislah, 2012). Optimal workload conditions are important for the health of the single individual and in order to assure the safety of other persons. A valid and reliable method for measuring mental workload would offer a way for achieving such conditions in human-machine systems by capturing the instantaneous workload continuously over time (Byrne and Parasuraman, 1996; Scerbo et al, 2001; Arico et al, 2017). It is important that the registration method does not interact with the task or alter subject’s mental state by imposing additional demands as it is the case during subjective assessment of workload by means of questionnaires. Questionnaires and performance evaluation are only of limited relevance for real-time analysis of workload conditions in the range of seconds
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