Investigating the relationship between EEG features and N-back task difficulty levels with NASA-TLX scores among undergraduate students

Abstract: For safe and efficient human-machine interactions, the amount of mental resources required by the task should not exceed available capacity of the person. Therefore, determination of mental workload has critical importance in the fields of human factors and ergonomics. Because of its temporal dependability, EEG data has become widely used in assessing and measuring mental workload in recent years. Accordingly, motivation of the study was to examine the role of brain-related data in discriminating mental workload levels. The current paper presented a statistically analysis of whether pre-determined task difficulty levels led to the intended mental workload manipulation. It was aimed to investigate the relationship between EEG features, task difficulty levels, subjective self-assessment (NASA-TLX) scores and performance measures (accuracy rate and latency). N-back tasks have been commonly used in the literature. In this study, n-back memory tests were performed at four different difficulty levels. As the number of n increases, so does the difficulty of the task. Tests were conducted on 25 (13 male, 12 female) healthy undergraduate students. The statistical analysis was performed for two sets of data. The first dataset, which included 300 session-based samples, was conducted in order to examine the possible relationship between task difficulty levels, performance criteria, and subjective assessments of mental workload. The second dataset, on the other hand, was analyzed on the basis of stimulus and consisted of seventy EEG features (5 frequency band power for 14 channels) corresponding to recording samples. The categorical variable reflecting the difficulty level of n-back memory was selected as dependent variable. It was demonstrated how the band power varies in various regions of the brain depending on the degree of task difficulty. Significant differences between the genders were noted in terms of all variables considered. As the task difficulty level increased, both the workload perceived by the participants (rho > 0.7, p < 0.01) and the latency in response time (rho > 0.6, p < 0.01) significantly increased. Otherwise, the correct answer rate decreased as the task became more difficult (rho > 0.6, p < 0.01). The number of hits (correct answers by detecting the match) was found to be more correlated with the task difficulty level compared to number of correct rejects (correct answers by detecting the non-match). The workload and its sub-dimensions perceived by the participants and performance variables are also related to each other. In tests with longer response times, participants reported that they felt more workload (rho > 0.6, p < 0.01). Conversely, the number of correct answers decreased (rho > 0.6, p < 0.01). It was also found that there was a significant difference between all difficulty levels compared in pairs, in terms of almost all variables (p < 0.001). There was no significant difference between men and women in terms of performance measures. However, men were found to report higher NASA-TLX scores than women, especially on difficult tasks. As a result, significant relationships between data obtained through different methods encourage the use of these methods together for reliable analysis in future studies.

Keywords: Workload Assessment, EEG Analysis, N-Back Memory Tasks, Physiological Markers

DOI: 10.54941/ahfe1002828

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